Managing Clustered Data Using Hierarchical Linear Modeling

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 m...

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Published in:Journal of nutrition education and behavior 2012-05, Vol.44 (3), p.271-277
Main Authors: Warne, Russell T., PhD, Li, Yan, MS, McKyer, E. Lisako J., PhD, MPH, Condie, Rachel, BS, Diep, Cassandra S., MS, Murano, Peter S., PhD
Format: Article
Language:English
Subjects:
Biomedical Research - methods
Cluster Analysis
Data Analysis
Diet - statistics & numerical data
Eating Habits
Evaluation Methods
Feeding Behavior
Female
Food
Gastroenterology and Hepatology
hierarchical linear modeling
Humans
Infant
Internal Medicine
Linear Models
Male
multilevel models
Multivariate Analysis
Nutrition
nutrition behavior
Nutritional Sciences
Sampling
Statistical Analysis
Statistics
survey research
Violations
WIC program
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cited_by cdi_FETCH-LOGICAL-c460t-9a8e5246ca22e099b75d0314d3f4b6c5487077609c99b9e40a645479a67ebc513
cites cdi_FETCH-LOGICAL-c460t-9a8e5246ca22e099b75d0314d3f4b6c5487077609c99b9e40a645479a67ebc513
container_end_page 277
container_issue 3
container_start_page 271
container_title Journal of nutrition education and behavior
container_volume 44
creator Warne, Russell T., PhD
Li, Yan, MS
McKyer, E. Lisako J., PhD, MPH
Condie, Rachel, BS
Diep, Cassandra S., MS
Murano, Peter S., PhD
description 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.
doi_str_mv 10.1016/j.jneb.2011.06.013
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source ScienceDirect Freedom Collection; ERIC
subjects Biomedical Research - methods
Cluster Analysis
Data Analysis
Diet - statistics & numerical data
Eating Habits
Evaluation Methods
Feeding Behavior
Female
Food
Gastroenterology and Hepatology
hierarchical linear modeling
Humans
Infant
Internal Medicine
Linear Models
Male
multilevel models
Multivariate Analysis
Nutrition
nutrition behavior
Nutritional Sciences
Sampling
Statistical Analysis
Statistics
survey research
Violations
WIC program
title Managing Clustered Data Using Hierarchical Linear Modeling
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