ABSTRACT
This chapter explains the concepts and practices of triangulation and the integration of findings in mixed-methods research. It defines multiple forms of triangulation (including methodological, data, theoretical, and investigator triangulation) and discusses how using different approaches or data sources can cross-verify results to build a more holistic understanding of the research question. Strategies for weaving together quantitative and qualitative evidence are highlighted – for example, employing joint displays or matrices to merge statistical results with thematic insights, examining where findings converge for reinforcement, and probing any divergent outcomes for deeper meaning. Guidance is provided on handling conflicting evidence in a balanced, reflexive manner so that an integrated interpretation remains coherent and credible. The chapter also considers modern tools (such as qualitative data software and emerging AI-based techniques) that can aid in combining multi-modal datasets, while emphasizing that the researcher’s interpretive judgment is ultimately crucial. Overall, this chapter prepares readers to effectively synthesize multiple strands of evidence, demonstrating how a well-executed integration can yield conclusions that are more robust and insightful than separate analyses alone.
