Conceptual models to guide integration during analysis in convergent mixed methods studies

Abstract

Methodologists have offered general strategies for integration in mixed-methods studies through merging of quantitative and qualitative data. While these strategies provide researchers in the field general guidance on how to integrate data during mixed-methods analysis, a methodological typology detailing specific analytic frameworks has been lacking. The purpose of this article is to introduce a typology of analytical approaches for mixed-methods data integration in mixed-methods convergent studies. We distinguish three dimensions of data merging analytics: (1) the relational dimension, (2) the methodological dimension, and (3) the directional dimension. Five different frameworks for data merging relative to the methodological and directional dimension in convergent mixed-methods studies are described: (1) the explanatory unidirectional approach, (2) the exploratory unidirectional approach, (3) the simultaneous bidirectional approach, (4) the explanatory bidirectional approach, and (5) the exploratory bidirectional approach. Examples from empirical studies are used to illustrate each type. Researchers can use this typology to inform and articulate their analytical approach during the design, implementation, and reporting phases to convey clearly how an integrated approach to data merging occurred.