An Introduction to Multilevel Modeling in Health Psychology Using R
DOI:
https://doi.org/10.22544/rcps.v44i02.10Keywords:
Health Psychology, Health behavior, Physical activity, Multilevel analysis, Multilevel regressionAbstract
The use of conventional statistical techniques, such as analysis of variance (ANOVA) or ordinary least squares regression, can lead to erroneous conclusions and biased results when there is nested data, such as patients in hospitals or adults in neighborhoods. Multilevel modeling allows this complexity to be addressed by examining relationships between variables at different levels of a hierarchical data structure. This article describes the basic concepts of multilevel analysis through applications in health psychology using the program R. Different multilevel regression models are illustrated using simulated data. The materials are available online. The results of the analysis represent the predictive between-group and within-group effects of neighborhood exercise area availability and behavioral intention on physical activity in adults sampled from different neighborhoods. The implementation of multilevel models can contribute to the understanding of behavior change and intervention strategies for the prevention of chronic diseases.References
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