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Although the epistemological arguments of the ''paradigm wars'' sharpened our thinking about issues related to mixed methodology, their lingering legacy has been to slow the progress of integration of methods. All mixed methods studies, by definition, attempt some form of integration, but the paradigm debates have made many researchers nervous about integrating the various strands of their research before they reach the point of drawing conclusions. There has, indeed, been a degree of illogic in the way some researchers have dealt with the issue of integration of data sources and analyses, where it has been considered epistemologically unacceptable to combine these, and yet desirable to corroborate or integrate conclusions drawn from data generated through diverse perspectives. In any case, as noted many years ago by Miles and Huberman (1994), these arguments are largely unproductive. From a pragmatic perspective, the primary issue is to determine what data and analyses are needed to meet the goals of the research and answer the questions at hand. Alternatively, a realist perspective encourages one to seek both process-and variable-oriented data to both detect regularities and understand the mechanisms by which they occur (Maxwell, 2008). The Continuum of Qualitative and QuantitativeRecent writing has tended to present conflicting rhetoric, advice, and practice on the issue of integration. The rhetoric that it is desirable to combine qualitative and quantitative elements at all stages of a mixed methods project is often matched by advice that one should conduct each of these elements separately prior to any combination of elements. In describing their approach to concept analysis as an integrative mixed method, Kane and Trochim (2007) suggest that Rather than simply combining qualitative and quantitative methods, [concept analysis] challenges the distinction between these two and suggests that they may indeed be more deeply intertwined. In some sense it is a method that supports the notion that qualitative information can be well represented quantitatively and that quantitative information rests upon qualitative judgment. (p. 177, reviewed in JMMR by Dixon, 2009

The approach taken to integration of diverse data sources and analytical approaches in mixed methods studies is a crucial feature of those studies. Models of integration in analysis range from discussing separately generated results from different components or phases of a study together as part of the conclusion, through synthesis of data from these different components, to combination of data sources or conversion of data types to build a blended set of results. Although different models of integration are appropriate for different research settings and purposes, an overcautious approach to integration can generate invalid or weakened conclusions through a failure to consider all available information together. Strategies for making the most of opportunities to integrate process and variable data in analysis to build strong and useful conclusions are identified and illustrated through reference to a variety of mixed methods studies, including several with a focus on transition to school.

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