Using multilevel modeling in caregiving research

Recently, caregiving research has moved towards a greater emphasis on the interactive and dynamic processes of the care situation. As a result, many of the questions are multilevel in nature, involving more than one unit of analysis and placing greater focus on the context of the care dyad. Nevertheless, most caregiving studies use methods that fail to address the hierarchical nature of the care dyad and consequently fail to illuminate variation both within and between dyad processes. The focus of this paper is to promote a dyad approach to the analysis of caregiving data and to highlight the advantages and appropriateness of multilevel modeling when dealing with clustered or hierarchical data. In particular, we discuss how multilevel modeling can be adapted to study change in the care dyad over time, improve the way we evaluate interventions, and enhance our understanding of dyad congruence.