Traditional study designs, such as individual-level studies and ecological studies, are unable to simultaneously examine the effects of individual-level and group-level factors on risk of disease. Multilevel analysis overcomes this limitation by allowing the simultaneous investigation of factors defined at multiple levels. Areas in which multilevel modeling can be applied to sexually transmitted infection (STI) research include examining how both group-level and individual-level factors are related to individual-level STI outcomes, assessing interactions between individual-level and group-level constructs, and exploring how factors at multiple levels contribute to group-to-group differences in rates of disease. In this article, we review the fundamentals of multilevel modeling, the applications of multilevel models for the examination of STIs, and the key challenges associated with using multilevel modeling for infectious-disease research.
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