Investigating multilevel mediation with fully or partially nested data

Mediation analysis has become one of the most widely used tools for investigating the mechanisms through which variables influence each other. When conducting mediation analysis with fully nested data (e.g., individuals working in teams) or partially nested data (e.g., individuals working alone in one study arm but working in teams in another arm) special considerations arise. In this article we (a) review traditional approaches for analyzing mediation in nested data, (b) describe multilevel structural equation modeling (MSEM) as a versatile technique for assessing mediation in fully nested data, and (c) explain how MSEM can be adapted for assessing mediation in partially nested data (MSEM-PN) and introduce two new MSEM-PN specifications. MSEM-PN affords options for testing equality of level-specific mediation effects in the nested arm with mediation effects in the nonnested arm. We demonstrate the application of MSEM and MSEM-PN in simulated examples from the group processes literature involving fully and partially nested data. Finally, we conclude by providing software syntax and guidelines for implementation.