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Qualitative data analysis: Analytic hierarchy

06/01/2018    hoangthuphuong   PHD Journey


The analytic hierarchy refers to the process through which qualitative 'findings' are built from the original raw data. It is described as a form of conceptual scaffolding within which the structure of the analysis is formed. The process is iterative and thus constant movement up and down the hierarchy is needed. The analytic process requires three forms of activity: data management in which the raw data are reviewed, labelled, sorted and synthesised; descriptive accounts in which the analyst makes use of the ordered data to identifying key dimensions, map the range and diversity of each phenomenon and develop classifications and typologies; and explanatory accounts in which the analyst builds explanations about why the data take the forms that are found and presented.
 
 
Source: Miles, M. B., Huberman, A. M., & Saldana, J. (2013). Qualitative data analysis. Sage.

CÁC BÀI VIẾT KHÁC CÙNG CHUYÊN ĐỀ

Computer-assisted qualitative methods
Computer-assisted qualitative methods
Weitzman (2000) provides the most up-to-date categorisation of CAQDAS software, building upon earlier work with Miles (cited above), which categorises software into five types:
Qualitative Data Analysis: Establishing typologies
Qualitative Data Analysis: Establishing typologies
To identify the relevant dimensions of a typology. Lazarsfield and Barton (1951) describe this as the 'dimensions which underlie the discrimination' made by the typology. For this, it is important for the analyst to have a strong familiarity with the data set and that tasks further down the analytic hierarchy, such as identifying the elements of a phenomenon and refining categories, have been completed.