SAGE Journal Articles
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Castro, F. G., Kellison, J. G., Boyd, S. J., & Kopak, A. (2010). A methodology for conducting integrative mixed methods research and data analysis. Journal of Mixed Methods Research, 4(4), 342–360. DOI:10.1177/1558689810382916.
Abstract: Mixed methods research has gained visibility within the last few years, although limitations persist regarding the scientific caliber of certain mixed methods research designs and methods. The need exists for rigorous mixed methods designs that integrate various data analytic procedures for a seamless transfer of evidence across qualitative and quantitative modalities. Such designs can offer the strength of confirmatory results drawn from quantitative multivariate analyses, along with “deep structure” explanatory descriptions as drawn from qualitative analyses. This article presents evidence generated from over a decade of pilot research in developing an integrative mixed methods methodology. It presents a conceptual framework and methodological and data analytic procedures for conducting mixed methods research studies, and it also presents illustrative examples from the authors’ ongoing integrative mixed methods research studies.
Collins, K. M. T., Onwuegbuzie, A. J., & Jiao, Q. G. (2007). A mixed methods investigation of mixed methods sampling designs in social and health science research. Journal of Mixed Methods Research, 1 (3), 267–294. DOI: 10.1177/1558699807299526
Abstract: A sequential design utilizing identical samples was used to classify mixed methods studies via a two-dimensional model, wherein sampling designs were grouped according to the time orientation of each study's components and the relationship of the qualitative and quantitative samples. A quantitative analysis of 121 studies representing nine fields in the social or health sciences revealed that more studies utilized a sampling design that was concurrent (66.1%) than sequential (33.9%). Also, identical sampling designs were the most prevalent, followed by nested sampling, multilevel sampling, and parallel sampling, respectively. Qualitative analysis suggested that across a number of studies the researchers made statistical generalizations that were not sufficiently warranted—culminating in interpretive inconsistency and contributing to crises of representation, legitimation, integration, and politics.