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Integrative Analysis Strategies for Mixed Data Sources

American Behavioral ScientistPublished 17 November 2011
Pat Bazeley
Citations204
SJR quartileQ1
SJR score0.96
SNIP1.51

TL;DR

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.

Abstract

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.

Keywords

Mathematics