On Quantitizing

By M. Sandelowski, Corrine Voils, George J. Knafl. Journal of Mixed Methods Research, 2009

636 citations recorded by the source corpus.

Quantitizing, commonly understood to refer to the numerical translation, transformation, or conversion of qualitative data, has become a staple of mixed methods research. Typically glossed are the foundational assumptions, judgments, and compromises involved in converting disparate data sets into each other and whether such conversions advance inquiry. Among these assumptions are that qualitative and quantitative data constitute two kinds of data, that quantitizing constitutes a unidirectional process essentially different from qualitizing, and that counting is an unambiguous process. Among the judgments are deciding what and how to count. Among the compromises are balancing numerical precision with narrative complexity. The standpoints of ``conditional complementarity,'' ``critical remediation,'' and ``analytic alternation'' clarify the added value of converting qualitative data into quantitative form.

Subfields: History and Philosophy of Science, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/b661cf11bbc2ff5ab4d8d15782ff135df5d6165b

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In Sociology and Political Science

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Citations in the corpus

• Mixed methods research synthesis: definition, framework, and potential (2011, background): “1999; Mitchell 1999), although sometimes data from qualitative studies are transformed to be incorporated in these syntheses as well (Johnson and Onwuegbuzie 2004; Sandelowski et al. 2009).”