2012
DOI: 10.1177/1558689812437101
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Triangulation and Mixed Methods Designs

Abstract: Data integration is a crucial element in mixed methods analysis and conceptualization. It has three principal purposes: illustration, convergent validation (triangulation), and the development of analytic density or ''richness.'' This article discusses such applications in relation to new technologies for social research, looking at three innovative forms of data integration that rely on computational support: (a) the integration of geo-referencing technologies with qualitative software, (b) the integration of… Show more

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Cited by 263 publications
(92 citation statements)
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References 33 publications
(35 reference statements)
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“…We used data integration in the analysis of WC to illustrate and cross-validate the information related JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION to the occurrence of the WC (Fielding, 2012). The information collected from the government and media sources was combined to create a database of WC.…”
Section: Discussionmentioning
confidence: 99%
“…We used data integration in the analysis of WC to illustrate and cross-validate the information related JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION to the occurrence of the WC (Fielding, 2012). The information collected from the government and media sources was combined to create a database of WC.…”
Section: Discussionmentioning
confidence: 99%
“…At each phase, the researcher shared results with staff and used data to support service reform. By linking quantitative measures to qualitative findings through a data matrix grid (Fielding, 2012), directors were able to contextualized youth experiences to outcomes on the quantitative measures.…”
Section: Model 2 a Transformative Mixed Methods Evaluationmentioning
confidence: 99%
“…Also referred to as 'triangulation' , this process can help to corroborate findings. It can also generate a deeper and more complete understanding of the area of study [36].…”
Section: Data Collectionmentioning
confidence: 99%