Quantifying Thematic Saturation in Qualitative Data Analysis

Dados Bibliográficos

ID2407552
AutoresAndrew Lowe (0000-0002-3307-1150, Auckland University of Technology, autor correspondente), Anthony C Norris (Auckland University of Technology), A Jane Farris (Auckland University of Technology), A Farris (Auckland University of Technology), Duncan R Babbage (0000-0002-9259-9246, Auckland University of Technology)
Ano2018
Volume30
Fascículo3
Páginas191-207
Data de publicação2018-08-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoCAM (JOURNAL)
Identificadores do periódicoISSN: 1087-8513 • E-ISSN: 1552-3969
EditoraSAGE Publications Inc (PUBLISHER)
DOI10.1177/1525822x17749386
OpenAlexW2793149982
IdiomaEN
Citações recebidas65
Referências citadas17

An important aspect of qualitative research is reaching saturation-loosely, a point at which observing more data will not lead to discovery of more information related to the research questions. However, there has been no validated means of objectively establishing saturation. This article proposes a novel quantitative approach to measuring thematic saturation based on a sound statistical model. The model is validated on two data sets from different qualitative research projects involving interviews, focus groups, and literature surveys. The proposed model provides consistent estimates of saturation across data sets, within branches of data sets, and over the course of a research project. The model can be used for both quantifying saturation and estimating the number of observations required to achieve a specified level of saturation

Data collection · Data mining · Data science · Qualitative research · Saturation (graph theory) · Sociology · Statistics · Computer Science · Mathematics · Qualitative Comparative Analysis Research · Qualitative Research Methods and Applications · Qualitative Research Methods and Ethics