Qual Data Analysis with Software
by Janet Salmons, Ph.D., Research Community Manager for Sage Methodspace
Qualitative researchers often collect large quantities of data that can include visuals or media, audio files or notes from interviews, text or artifacts. Software can aid the process and help organize, manage, and code data.
This use of technology is described as CAQDAS, Computer Assisted Qualitative Data AnalysiS. Microsoft Office software, including Word and Excel are adapted for research uses, or researchers use specific programs, such as NVivo, Atlas T.I., HyperRESEARCH and others.
In this post you will find a collection of open access articles with how-to steps and examples.
A Multidisciplinary Collection of Open Access Articles about Using CAQDAS
Giesen, L., & Roeser, A. (2020). Structuring a Team-Based Approach to Coding Qualitative Data. International Journal of Qualitative Methods, 19. https://doi.org/10.1177/1609406920968700
Abstract. Improvements to qualitative data analysis software (QDAS) have both facilitated and complicated the qualitative research process. This technology allows us to work with a greater volume of data than ever before, but the increased volume of data frequently requires a large team to process and code. This paper presents insights on how to successfully structure and manage a team of staff in coding qualitative data. We draw on our experience in team-based coding of 154 interview transcripts for a study of school meal programs. The team consisted of four coders, three senior reviewers, and a lead analyst and external qualitative methodologist who shepherded the coding process together. Lessons learned from this study include: 1) establish a strong and supportive management structure; 2) build skills gradually by breaking training and coding into “bite-sized” pieces; and 3) develop detailed reference materials to guide your coding team.
González Canché, M. S. (2023). Graphical Retrieval and Analysis of Temporal Information Systems (GRATIS): An Integrative Mixed Methodology and Open-Access Software to Analyze the (Non-)Linear Chronological Evolution of Information Embedded in Textual/Qualitative Data. Journal of Mixed Methods Research, 0(0). https://doi.org/10.1177/15586898231166968
Abstract. Like a video that reveals much more than a single photo, the incorporation of time to the analysis of qualitative evidence promotes contextualized understandings and allows research participants and readers to interactively review the processes and rationale that researchers followed to craft their findings and conclusions. However, mixed methods and qualitative methodologies available today forfeit the nuances gained by analyzing the chronological/temporal evolution of processes. We contribute to mixed methods research by introducing graphical retrieval and analysis of temporal information systems (GRATIS), a methodology (and open-access software) designed to visualize and analyze the time-based richness embedded in all qualitative/textual data. GRATIS employs dynamic network visualizations and data science mining/retrieval tools to combat the assumption that longitudinal studies require large timespans. We showcase how all qualitatively- or machine-learning-coded textual data may be analyzed with no extra feature engineering (i.e., data cleaning or preparation), rendering fully integrative/interactive outputs that strengthen the transparency of our findings and conclusions and open the “analytic black box” that characterizes most of mixed methods and qualitative studies to date. GRATIS contributes to democratizing data science by removing financial and computer programming barriers to benefit from data science applications. All data and software to replicate the analyses are provided with this submission.
Maher, C., Hadfield, M., Hutchings, M., & de Eyto, A. (2018). Ensuring Rigor in Qualitative Data Analysis: A Design Research Approach to Coding Combining NVivo With Traditional Material Methods. International Journal of Qualitative Methods, 17(1). https://doi.org/10.1177/1609406918786362
Abstract. Deep and insightful interactions with the data are a prerequisite for qualitative data interpretation, in particular, in the generation of grounded theory. The researcher must also employ imaginative insight as they attempt to make sense of the data and generate understanding and theory. Design research is also dependent upon the researchers’ creative interpretation of the data. To support the research process, designers surround themselves with data, both as a source of empirical information and inspiration to trigger imaginative insights. Constant interaction with the data is integral to design research methodology. This article explores a design researchers approach to qualitative data analysis, in particular, the use of traditional tools such as colored pens, paper, and sticky notes with the CAQDAS software, NVivo for analysis, and the associated implications for rigor. A design researchers’ approach which is grounded in a practice which maximizes researcher data interaction in a variety of learning modalities ensures the analysis process is rigorous and productive. Reflection on the authors’ research analysis process, combined with consultation with the literature, would suggest digital analysis software packages such as NVivo do not fully scaffold the analysis process. They do, however, provide excellent data management and retrieval facilities that support analysis and write-up. This research finds that coding using traditional tools such as colored pens, paper, and sticky notes supporting data analysis combined with digital software packages such as NVivo supporting data management offer a valid and tested analysis method for grounded theory generation. Insights developed from exploring a design researchers approach may benefit researchers from other disciplines engaged in qualitative analysis.
O’Kane, P., Smith, A., & Lerman, M. P. (2021). Building Transparency and Trustworthiness in Inductive Research Through Computer-Aided Qualitative Data Analysis Software. Organizational Research Methods, 24(1), 104–139. https://doi.org/10.1177/1094428119865016
Abstract. Many scholars have called for qualitative research to demonstrate transparency and trustworthiness in the data analysis process. Yet these processes, particularly within inductive research, often remain shrouded in mystery. We suggest that computer-aided/assisted qualitative data analysis software (CAQDAS) can support qualitative researchers in their efforts to present their analysis and findings in a transparent way, thus enhancing trustworthiness. To this end, we propose, describe, and illustrate working examples of six CAQDAS building blocks, three combined CAQDAS techniques, and two coder consistency checks. We argue that these techniques give researchers the language to write about their methods and findings in a transparent manner and that their appropriate use enhances a research project’s trustworthiness. Specific CAQDAS techniques are rarely discussed across an array of inductive research processes. Thus, we see this article as the beginning of a conversation about the utility of CAQDAS to support inductive qualitative research.
Sal Moslehian, A., Tucker, R., & Kocaturk, T. (2022). Diagrammatic Modelling Tools for Grounded Theory Research: The Implementation of a Multi-Representational Approach. International Journal of Qualitative Methods, 21. https://doi.org/10.1177/16094069221127069
Abstract. Grounded Theory (GT) researchers have an ever-expanding palette of digital tools available to further analyse complex phenomena with interrelated data sets. However, few GT researchers have systematically examined how the use of diagramming tools can enhance analysis. To advance the analytical process of GT, this study develops a multi-representational approach that integrates with research design. After diagrams supportive of GT are identified for their potential improvements to the analytical process, the research focuses on the experience of employing three diagramming tools (Flourish, Observable, and Pajek) in developing two complementary diagrams (Network and Arc diagrams). The use of these tools for analysis is explained in detail for conducting extensive constructivist GT study; illustrated via a case study examining a century of innovation in hospital design. Via this multiple-source case study, this paper demonstrates how the sagacious deployment of diagramming tools, when carefully aligned to research objectives, can complement GT analysis by facilitating systematic thinking and holistic interpretation of hidden patterns.
Watkins, D. C. (2017). Rapid and Rigorous Qualitative Data Analysis: The “RADaR” Technique for Applied Research. International Journal of Qualitative Methods, 16(1). https://doi.org/10.1177/1609406917712131
Abstract. Despite the advantages of using qualitative data to advance research and practice, applied researchers agree that the most daunting task is trying to analyze the data rapidly and rigorously. This article introduces a quick and comprehensive qualitative analysis strategy called the rigorous and accelerated data reduction (RADaR) technique. The RADaR technique involves using tables and spreadsheets from general purpose, word processing software to develop all-inclusive data tables that undergo several revisions. These revisions, called “data reduction,” help produce shorter, more concise data tables. The RADaR technique converts raw, textual data into a more manageable and user-friendly format. It is rigorous because of the systematic analysis that occurs during each step of the process, and it is accelerated because the time required to review and reduce each phase of the data table becomes shorter as the user produces more condensed and concise presentations of the textual data. [Note: this article discusses Microsoft Word and Excel.]
More Methodspace Posts about Qualitative Data Analysis
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