Integrating and Consolidating Data in Mixed Methods Data Analysis: Examples From Focus Group Data With Children

Abstract

The challenge in data analysis often lies in accounting for the multidimensionality and complexity of the data while simultaneously discovering patterns. Integrating and consolidating different types of data during analysis can broaden the perspective and permit obtaining complementary views. This methodological research study on data collection illustrates how one type of data collection generates different types of data, which can be linked and consolidated to reach a better understanding of the topic. Procedures and practicalities are illustrated to offer a good practice example for data integration and consolidation. With the methodological reflection of research practice, I evaluate the consequences for the field of mixed methods research, in which the practicalities of an integrated mixed analysis still need to be elaborated.

Virtual Special Issue on “Integration in Mixed Methods Research”

“…Vogl (2019) discussed mixed methods data analysis and provided a novel study describing the analysis of focus group data. This study is rather unique in that she collected data using a single method, focus groups, yet conducted a mixed data analysis that integrated qualitative and quantitative characteristics (e.g., content of discussion and word counts) along with a third strand focused on the interaction.…”

Approaches to interdisciplinary mixed methods research in land‐change science and environmental management

“…1989; Creswell et al. 2006; Teddlie & Tashakkori 2006; Vogl 2019). Among these preestablished coding themes, we identified and revised themes that best differentiated the methodological approaches in our sample articles.…”

“…For example, some existing typologies focus on the degree to which integration occurs, a principal difference among mixed methods studies. Vogl (2019:537) discusses the difference between data combination and integration, noting that when data are combined, the elements are independent, whereas integrative methods create a “joint product” and each source of data “aims for the same research objective.” Similar differentiations (with slightly different terminology) occur in Cheong et al. (2012) for complementarity and integration designs and in Yin (2006) for isolated and integrated designs.…”

Reframing Integration for Mixed Methods Research

“…A common orientation views the outcomes of integration as being related to improved knowledge or understanding (breadth, depth, and validity) as illustrated in the Fetters and Molina-Azorin (2017) definition presented above (see also, Bryman, 2008; Greene, Caracelli, & Graham, 1989; Heyvaert, Hannes, Maes, & Onghena, 2013; Johnson, Onwuegbuzie, & Turner, 2007; Sligo, Nairn, & McGee, 2018; Vogl, 2019). Within this perspective the meaning of knowledge or understanding is seldom explored, and neither the political nor social dimensions of understanding are usually considered.…”