The Constant Comparative Method, while deeply rooted in classical Grounded Theory, extends its reach far beyond. It’s a powerful and frequently employed analytical approach in qualitative research, offering a systematic way to explore and understand data across diverse methodologies.
At its core, the constant comparative method is fundamentally intuitive: to comprehend qualitative data, comparison is essential. This comparison might involve contrasting interviews with different participants, analyzing variations between respondent groups, or even examining diverse segments of data within established codes or themes. The essence lies in uncovering differences and similarities within the data, ultimately illuminating the underlying narratives and reasons behind these variations.
As Tesch (1990) aptly points out, comparison is the cornerstone of category and thematic refinement in qualitative research:
“Comparing and contrasting is used for practically all intellectual tasks during analysis: forming categories, establishing the boundaries of the categories, assigning the segments to categories, summarizing the content of each category, finding negative evidence, etc. The goal is to discern conceptual similarities, to refine the discriminative power of categories, and to discover patterns.” (Tesch, 1990)
Beyond a mere analytical technique, the constant comparative method also functions as a robust methodology. It guides ongoing sampling and participant recruitment, ensuring diverse perspectives are included to enrich comparisons and delve deeper into emerging themes. To fully appreciate its significance, let’s explore its origins and evolution.
Origins of the Constant Comparative Method
The term “Constant Comparative Method” was formalized within Glaser and Strauss’s (1967) seminal work on Grounded Theory. However, its conceptual roots trace back to an earlier article by Glaser (1965). This method emerged as a bridge between comprehensive thematic coding and theory generation in qualitative analysis. Glaser and Strauss argued that overly rigid, exhaustive coding could stifle hypothesis generation. Conversely, relying solely on data inspection without systematic coding might lead to superficial analysis.
Their proposed solution was a hybrid approach: the constant comparative method. This involves iteratively re-examining codes as new data emerges, constantly seeking commonalities and differences. This continuous process of comparison facilitates the organic development and refinement of theory, ensuring a more systematic and rigorous analysis.
“Systematizing the second approach [pure grounded theory with no coding] by this method does not supplant the skills and sensitivities required in inspection. Rather the constant comparative method is designed to aid analysts with these abilities in generating a theory which is integrated, consistent, plausible, close to the data” (Glaser, 1965).
While terms like ‘systematizing’ and ‘consistent’ may be viewed as overly positivist by some qualitative researchers, the core strength of the constant comparative method lies in its commitment to staying ‘close to the data’. In contrast to purely inductive approaches that might rely on abstracted interpretations, constant comparison compels researchers to remain deeply engaged with the data, attending meticulously to participant voices and experiences. This rigorous engagement minimizes reliance on researchers’ pre-conceived notions or potentially biased interpretations.
However, it is crucial to understand that this ‘systematizing’ is not intended to produce a single, definitive interpretation. As Glaser (1965) clarifies:
“the constant comparative method is not designed (as methods of quantitative analysis are) to guarantee that two analysts working independently with the same data will achieve the same result” (Glaser, 1965).
Instead, the constant comparative method aims to generate a multitude of hypotheses, potentially diverse and even initially contradictory, around a central research issue. For researchers seeking to develop and rigorously test a singular, precise theory, Glaser recommends analytic induction, a distinct methodological approach better suited for such focused theory testing, and a topic for another discussion.
Stages of the Constant Comparative Method
Glaser (1965) outlines four key stages in the constant comparative method, which essentially encompass the entire qualitative analysis process:
-
Comparing incidents applicable to each category: This initial stage involves open coding, where data is meticulously examined, and initial codes are developed to categorize incidents or pieces of information. The core of this stage is constant comparison: each new incident is compared with previous incidents within the same category. This comparison helps refine the properties of the category, identify variations, and explore the dimensions of the concept being coded.
Initial coding process in qualitative research -
Integrating categories and their properties: As coding progresses, categories begin to emerge and develop. This stage focuses on identifying relationships between categories and their properties. Through continued comparison, researchers look for connections, overlaps, and potential hierarchies among categories. This integration helps build a more coherent and nuanced understanding of the phenomena being studied.
-
Delimiting the theory: With categories and their relationships becoming clearer, the focus shifts to delimiting the emerging theory. This involves refining the scope of the theory, identifying core categories, and reducing the number of less relevant categories. Constant comparison at this stage helps to determine which categories are most central to the developing theory and which can be considered secondary or peripheral.
-
Writing the theory: The final stage involves articulating and writing up the developed theory. This is not simply a summary of findings but a coherent and integrated explanation of the phenomena under investigation, grounded in the data analysis process. The constant comparative method ensures that the theory remains closely tied to the data, providing a rich and empirically supported account.
These stages, while presented linearly, are inherently iterative. Qualitative research is rarely a strictly linear process. Approaches like Grounded Theory and Thematic Analysis emphasize cyclical phases of analysis, such as open and axial coding. The term “constant” in constant comparative method highlights that comparison should be an ongoing and frequent activity throughout the entire research process, not merely a final step.
It’s tempting to relegate comparison to convenient breakpoints, such as after coding a complete interview or a set of sources. However, the true power of the constant comparative method lies in its continuous application. Even within a single source, new statements or insights can challenge emerging codes or theoretical understandings. This necessitates immediate reflection and comparison with other parts of the data, ensuring the analysis remains dynamic and responsive to the nuances of the data. Qualitative Data Analysis Software (QDAS) like Quirkos is specifically designed to facilitate this rapid comparison, keeping researchers closely connected to their data throughout the analysis.
Benefits and Applications Beyond Grounded Theory
While demanding in terms of time and intellectual engagement, the constant comparative method offers significant rewards. This rigorous and iterative process of reading and cross-examining data is what empowers qualitative research to challenge assumptions, disrupt the status quo, and drive meaningful change.
It’s important to remember that:
“Comparison can often be based on memory. Usually there is no need to refer to the actual note on every previous incident for each comparison.” Glaser and Strauss (1967).
This highlights the crucial role of researcher immersion in the data. Through constant engagement and comparison, researchers develop an intimate familiarity with their data, which is essential for skillful code development and thematic analysis.
Because of its inherent iterative nature and its influence on ongoing data collection, the constant comparative method transcends a mere analytical technique; it shapes the entire research methodology, particularly the sampling process. Constant comparison should actively guide the recruitment of new participants with diverse experiences, specifically chosen to explore emerging contradictions, uncertainties, and refine codes and hypotheses. This necessitates that analysis begins early in the data collection phase and continues iteratively, without rigid pre-conceived notions of sample size.
This iterative sampling and analysis directly relates to the concept of saturation in qualitative research. Saturation, in this context, is reached when the inclusion of new participants or data sources no longer yields novel insights or theoretical developments. While the concept of saturation has been critiqued as potentially positivistic (Low, 2019), Glaser’s notion of theoretical saturation focuses more on the depth and richness of the developing theory rather than simply sample size. Concepts like ‘information power’ (Malterud et al., 2016) offer alternative perspectives that essentially address similar concerns—the point at which further data collection provides diminishing returns for theoretical understanding.
Furthermore, the constant comparative method is not confined to Classical Grounded Theory (CGT). Its principles and techniques are readily applicable to various qualitative approaches, including thematic analysis, discourse analysis, and even later stages of Interpretative Phenomenological Analysis (IPA). Fram (2013) provides examples of its application across diverse methodologies, although interpretations and critiques of Classical Grounded Theory may vary. Exploring Glaser’s original paper on constant comparative analysis (1965) is highly recommended. It provides a clear, accessible explanation of the method and anticipates many of the theoretical and practical considerations still debated in contemporary qualitative research.
Finally, it’s crucial to distinguish the constant comparative method from Qualitative Comparative Analysis (QCA) (Ragin, 1998). QCA primarily focuses on comparing whole cases for macro-level analysis, while the constant comparative method is deeply rooted in within-case qualitative data analysis.
Conclusion: Embracing Constant Comparison in Qualitative Research
In summary, the constant comparative method encourages researchers to engage in multifaceted comparisons: within and between codes and themes, within and between data sources, and across participant groups based on demographics or roles. The overarching principle is that comparison is a continuous, iterative process aimed at developing and refining theory, not reducing qualitative analysis to quantitative measures.
While software tools (CAQDAS or QDAS) can streamline analysis, it’s essential to avoid the trap of focusing solely on numerical counts of codes or themes. The true essence of qualitative analysis lies in the qualitative comparison of data—reading, re-grouping, and iteratively challenging and refining emerging theories.
Quirkos is designed to prioritize qualitative engagement with data, minimizing the emphasis on quantitative summaries. Its query comparison mode facilitates side-by-side text analysis, making constant comparison quick and efficient. Whether comparing codes, groups, individuals, or inter-coder reliability, Quirkos supports a constant comparative approach. Quirkos Cloud further enhances this by enabling real-time team collaboration, simplifying constant comparison in collaborative projects.
We invite you to explore Quirkos through a free trial with no feature restrictions to assess its suitability for your qualitative research, regardless of whether you explicitly employ the constant comparative method. Explore our tutorials to see Quirkos in action across various qualitative methodologies.
References
Boeije, H. (2002). A Purposeful Approach to the Constant Comparative Method in the Analysis of Qualitative Interviews. Quality & Quantity, 36, 391–409. https://doi.org/10.1023/A:1020909529486
Fram, S. M. (2013). The Constant Comparative Analysis Method Outside of Grounded Theory. The Qualitative Report, 18(1). https://files.eric.ed.gov/fulltext/EJ1004995.pdf
Glaser, B. G. (1965). The Constant Comparative Method of Qualitative Analysis. Social Problems, 12(4), 436-445.
Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine De Gruyter. http://books.google.com/books?hl=en&lr=&id=tSi7KiOHkpYC&oi=fnd&pg=PP13&sig=YqsrlNtwte1BiQQiLKUJ29ep0OA&dq=Basics+of+Qualitative+Research%3A+Grounded+Theory+Procedures+and+Techniques&prev=http%3A%2F%2Fscholar.google.com%2Fscholar%3Fq%3DBasics%2Bof%2BQualitative%2BResearch%3A%2BGrounded+Theory%2BProcedures%2Band%2BTechniques%26num%3D100%26hl%3Den%26lr%3D%26sa%3DG&ref=quirkos.com
Low, J. (2019). A pragmatist perspective on the problem of saturation in qualitative research. Sociological Focus, 52(2), 141-154. https://www.tandfonline.com/doi/abs/10.1080/00380237.2018.1544514?journalCode=usfo20&ref=quirkos.com
Malterud, K., Siersma, V. D., & Guassora, A. D. (2016). Sample Size in Qualitative Interview Studies: Guided by Information Power. Qualitative Health Research, 26(12), 1753–1760. https://journals.sagepub.com/doi/abs/10.1177/1049732315617444?journalCode=qhra&ref=quirkos.com
Ragin, C. C. (1998). The logic of qualitative comparative analysis. International Review of Social History, 43(S6), 81-98. https://www.cambridge.org/core/services/aop-cambridge-core/content/view/27BE4FF14356F5EDB9FD2E32701FFD96/S0020859000115111a.pdf/div-class-title-the-logic-of-qualitative-comparative-analysis-div.pdf?ref=quirkos.com
Tesch, R. (1990). Qualitative research: Analysis types and software tools. Falmer, New York.
