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
Journal article
Cerin, Ester. (2011). 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. Journal of Planning Literature. 26(2), pp. 151 - 167. https://doi.org/10.1177/0885412210386229
Authors | Cerin, Ester |
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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. |
Year | 2011 |
Journal | Journal of Planning Literature |
Journal citation | 26 (2), pp. 151 - 167 |
ISSN | 0743-1635 |
Digital Object Identifier (DOI) | https://doi.org/10.1177/0885412210386229 |
Page range | 151 - 167 |
Research Group | Institute for Health and Ageing |
Publisher's version | File Access Level Controlled |
https://acuresearchbank.acu.edu.au/item/858q4/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
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