Cargando…
Indicator-driven data calibration of expert interviews in a configurational study
Expert interviews can provide interesting data for the use in qualitative comparative analysis (QCA) to investigate complex social phenomena. To guide the challenging task of data calibration from qualitative data sets, techniques have already been suggested for the transformation of qualitative dat...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108532/ https://www.ncbi.nlm.nih.gov/pubmed/35586724 http://dx.doi.org/10.1016/j.mex.2022.101699 |
_version_ | 1784708725987082240 |
---|---|
author | Naims, Henriette Eppinger, Elisabeth |
author_facet | Naims, Henriette Eppinger, Elisabeth |
author_sort | Naims, Henriette |
collection | PubMed |
description | Expert interviews can provide interesting data for the use in qualitative comparative analysis (QCA) to investigate complex social phenomena. To guide the challenging task of data calibration from qualitative data sets, techniques have already been suggested for the transformation of qualitative data into fuzzy sets. The current article follows existing guidelines and extends them with a system for indicator-based data calibration of expert interviews. While the underlying data set is confidential due to its corporate setting, in this article the analysis of the data is made transparent and hence reproducible for potential follow-up studies. First, the process of data collection is described, and the final data sample is characterized. Consequently, a system for indicator-based data calibration is presented and the calibration results for the empirical sample are provided in form of the set membership of cases and truth tables. • Data collection from expert interviews is described for a configurational setting • A combined indicator-based system is used for the calibration of qualitative data |
format | Online Article Text |
id | pubmed-9108532 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-91085322022-05-17 Indicator-driven data calibration of expert interviews in a configurational study Naims, Henriette Eppinger, Elisabeth MethodsX Method Article Expert interviews can provide interesting data for the use in qualitative comparative analysis (QCA) to investigate complex social phenomena. To guide the challenging task of data calibration from qualitative data sets, techniques have already been suggested for the transformation of qualitative data into fuzzy sets. The current article follows existing guidelines and extends them with a system for indicator-based data calibration of expert interviews. While the underlying data set is confidential due to its corporate setting, in this article the analysis of the data is made transparent and hence reproducible for potential follow-up studies. First, the process of data collection is described, and the final data sample is characterized. Consequently, a system for indicator-based data calibration is presented and the calibration results for the empirical sample are provided in form of the set membership of cases and truth tables. • Data collection from expert interviews is described for a configurational setting • A combined indicator-based system is used for the calibration of qualitative data Elsevier 2022-04-26 /pmc/articles/PMC9108532/ /pubmed/35586724 http://dx.doi.org/10.1016/j.mex.2022.101699 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Method Article Naims, Henriette Eppinger, Elisabeth Indicator-driven data calibration of expert interviews in a configurational study |
title | Indicator-driven data calibration of expert interviews in a configurational study |
title_full | Indicator-driven data calibration of expert interviews in a configurational study |
title_fullStr | Indicator-driven data calibration of expert interviews in a configurational study |
title_full_unstemmed | Indicator-driven data calibration of expert interviews in a configurational study |
title_short | Indicator-driven data calibration of expert interviews in a configurational study |
title_sort | indicator-driven data calibration of expert interviews in a configurational study |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108532/ https://www.ncbi.nlm.nih.gov/pubmed/35586724 http://dx.doi.org/10.1016/j.mex.2022.101699 |
work_keys_str_mv | AT naimshenriette indicatordrivendatacalibrationofexpertinterviewsinaconfigurationalstudy AT eppingerelisabeth indicatordrivendatacalibrationofexpertinterviewsinaconfigurationalstudy |