Table 1.

Taxonomy of mixed method designs

Element	Category	Definition
Structure	QUAL → quan	Sequential collection and analysis of quantitative and qualitative data, beginning with qualitative data, for primary purpose of exploration/hypothesis generation
	qual → QUAN	Sequential collection and analysis of quantitative and qualitative data, beginning with qualitative data, for primary purpose of confirmation/hypothesis testing
	Quan → QUAL	Sequential collection and analysis of quantitative and qualitative data, beginning with quantitative data, for primary purpose of exploration/hypothesis generation
	QUAN → qual	Sequential collection and analysis of quantitative and qualitative data, beginning with quantitative data, for primary purpose of confirmation/hypothesis testing
	Qual + QUAN	Simultaneous collection and analysis of quantitative and qualitative data for primary purpose of confirmation/hypothesis testing
	QUAL + quan	Simultaneous collection and analysis of quantitative and qualitative data for primary purpose of exploration/hypothesis generation
	QUAN + QUAL	Simultaneous collection and analysis of quantitative and qualitative data, giving equal weight to both types of data
Function	Convergence	Using both types of methods to answer the same question, either through comparison of results to see if they reach the same conclusion (triangulation) or by converting a data set from one type into another (e.g. quantifying qualitative data or qualifying quantitative data)
	Complementarity	Using each set of methods to answer a related question or series of questions for purposes of evaluation (e.g., using quantitative data to evaluate outcomes and qualitative data to evaluate process) or elaboration (e.g., using qualitative data to provide depth of understanding and quantitative data to provide breadth of understanding)
	Expansion	Using one type of method to answer questions raised by the other type of method (e.g., using qualitative data set to explain results of analysis of quantitative data set)
	Development	Using one type of method to answer questions that will enable use of the other method to answer other questions (e.g., develop data collection measures, conceptual models or interventions)
	Sampling	Using one type of method to define or identify the participant sample for collection and analysis of data representing the other type of method (e.g., selecting interview informants based on responses to survey questionnaire)
Process	Merge	Merge or converge the two datasets by actually bringing them together (e.g., convergence—triangulation to validate one dataset using another type of dataset)
	Connect	Have one dataset build upon another data set (e.g., complementarity—elaboration, transformation, expansion, initiation or sampling)
	Embed	Conduct one study within another so that one type of data provides a supportive role to the other dataset (e.g., complementarity—evaluation: a qualitative study of implementation process embedded within an RCT of implementation outcome)