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Statistical approaches to testing the relationships of the built environment with resident-level physical activity behavior and health outcomes in cross-sectional studies with cluster sampling
Cerin, Ester
Cerin, Ester
Author
Abstract
To achieve valid conclusions, studies exploring associations of the built environment with residents' physical activity and health-related outcomes need to employ statistical approaches accounting for clustered data. This article discusses the following main statistical approaches: analysis of covariance, regression models with robust standard errors, generalized estimating equations, and multilevel generalized linear models. The choice of a statistical method depends on the characteristics of the study and research questions. While the first three approaches are employed to account for clustering in the data, multilevel models can also help unravel more substantive issues within a social ecological theoretical framework of health behavior.
Keywords
Date
2011
Type
Journal article
Journal
Journal of Planning Literature
Book
Volume
26
Issue
2
Page Range
151-167
Article Number
ACU Department
Mary MacKillop Institute for Health Research
Faculty of Health Sciences
Faculty of Health Sciences
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Open Access Status
License
File Access
Controlled