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Integrative Analysis Strategies for Mixed Data Sources

Integrative Analysis Strategies for Mixed Data Sources 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Behavioral Scientist SAGE

Integrative Analysis Strategies for Mixed Data Sources

American Behavioral Scientist , Volume 56 (6): 15 – Jun 1, 2012

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References (59)

Publisher
SAGE
Copyright
© 2012 SAGE Publications
ISSN
0002-7642
eISSN
1552-3381
DOI
10.1177/0002764211426330
Publisher site
See Article on Publisher Site

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.

Journal

American Behavioral ScientistSAGE

Published: Jun 1, 2012

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