Crossover analyses reveal complementarity between qualitative and quantitative results in survey research, suggesting new insights for data interpretation.
Crossover analyses are ways of mixing data across study strands from differing traditions, for example, transforming and analyzing qualitative strand data quantitatively together with the quantitative strand data. In response to a recent call for innovation with crossover analyses in mixed methods, this article contributes to the field of mixed methods research by presenting a method of crossover analysis in convergent mixed methods designs. Using survey data, contingency tables were used to merge dichotomized quantitative and qualitative strand results for mixed analysis and joint interpretation using Chi-square and odd ratio analyses. Ratings and open-ended comments about different aspects of the same phenomenon were integrated and explicitly linked with the rationale as means to achieve complementarity in the meta-inference.
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Hutchins et al. (2026) studied this question.
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