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Bridging Stata and ATLAS.ti: A mixed-methods workflow for assessing research quality through interview data

Author

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  • Daniel de Gracia Palomera

    (National University of Distance Education (UNED))

Abstract

Assessing the quality of social research often requires combining structured indicators with the rich, contextual evidence gathered through interviews, yet workflows linking quantitative software like Stata with qualitative platforms such as ATLAS.ti remain largely manual and poorly documented. This presentation introduces a reproducible pipeline that connects Stata with ATLAS.ti to support mixed-methods research on the quality of social research practices, using semi-structured interviews with researchers as the empirical case. The workflow shows how Stata can (1) organize and preprocess interview metadata (sample characteristics, coding frequencies, respondent profiles) exported from ATLAS.ti for descriptive and inferential analysis; (2) import code cooccurrence tables and thematic network outputs generated in ATLAS.ti to quantify patterns across interviews, complementing qualitative interpretation with statistical summaries; and (3) generate reproducible reports (do-files, dynamic documents) that integrate quotations, code frequencies, and quantitative indicators of research quality into a single analytical narrative. Drawing on an applied case examining perceptions of methodological rigor and questionable research practices among social scientists, this work illustrates how this Stata–ATLAS.ti integration strengthens triangulation, improves traceability, and reduces the friction typically involved in moving between qualitative and quantitative environments. The approach is adaptable to other disciplines combining interview-based and structured data.

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Handle: RePEc:boc:spai26:13
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