What Is Researcher Triangulation in Qualitative Analysis?
Researcher triangulation in qualitative analysis uses multiple researchers to collect and analyze data. In qualitative research, you can think of researcher triangulation as a type of data control.
Qualitative researchers use triangulation because their work is inherently interpretive in nature. Therefore, the reliability and validity of the results can be difficult to verify through a scientific, objective lens. The idea of researcher triangulation is that if different researchers use the same research technique and arrive at the same results, the reliability of that data increases.
In short, researcher triangulation democratizes the research process. It helps to avoid biases and limitations and also increases data reliability as opposed to using just one single researcher.
What is Triangulation?
The triangle being the strongest geometric shape, triangulation represents the concept of adding strength to data. That is to say, triangulation makes data more stable and reliable
In practice, triangulation uses three (or more) data points to corroborate information that converges on a single point. For example, triangulated surveying instruments generally use three static locations to determine the location of other objects.
The central premise of triangulation is that all sources confirm the collective results. As a result, those results are considered more accurate, more exact, and more reliable.
Other Types of Triangulation in Qualitative Research
Researcher triangulation is not the only type of triangulation used in qualitative research. Patton (1999) noted that triangulation refers to the use of multiple methods, data sources, [or researchers] to develop a comprehensive understanding of phenomena.
For example, data triangulation in qualitative research refers to using multiple data sources, such as interviews, observations, and documents, to comprehensively understand a topic. [1]
Another type is triangulation in mixed-method research. As the name suggests, it usually involves mixing qualitative and quantitative data to confirm your findings. You combine qualitative and quantitative methods to expand your evidence, improve the credibility of your findings, and validate the results from one method with the results from the other one.
Aside from researcher triangulation, data triangulation, and mixed-method triangulation, other ways to triangulate data in qualitative research include:
Peer debriefing: You discuss findings with colleagues or peers. Peer debriefers provide constructive feedback and help identify possible errors, biases, or oversights.
Participant validation: You share your research findings with the participants to confirm the accuracy of the data and your interpretation of the results.
Reflexivity: You reflect on your own assumptions, values, and biases that may affect your interpretation of data. This can also be referred to as bracketing in qualitative research. Reflexivity is not traditionally considered a form of triangulation (and would not be considered one by most journals). However, through the use of memos, one can consider bracketing as triangulation with one's past self.
One way to manage these tasks is often through memos. While you can memo by hand or a word processor, coding software like Delve organizes and streamlines the entire process for you.
Why Is Researcher Triangulation Important?
Researcher triangulation adds rigor to your study. With each researcher collecting and analyzing data, you can test all of the findings against one another. Corroborating data in this way helps lead to consensus results, which other researchers typically assume are more reliable.
Researcher diversity is another important factor of researcher triangulation. Incorporating diverse researchers across various ethnicities, ages, genders, and classes can help identify and minimize potential observer and interviewer bias.
Overall, the main goal of researcher triangulation is to increase the sturdiness and structural integrity of your work. All triangulation, for that matter, is an effective way to reduce the potential for error, bias, or misinterpretation in qualitative data analysis.
Tl;dr: “Why should I use researcher triangulation?”
Involving multiple researchers to collect and analyze data adds rigor to your study and confirms data reliability when the same research technique leads to the same findings.
Incorporating researcher triangulation improves reliability in qualitative studies that heavily rely on researcher interpretations to generate data.
Researcher triangulation renders consensus results that are typically assumed to be more reliable by other researchers.
Diversity in researcher triangulation can help minimize observer and interviewer bias.
How to Conduct Researcher Triangulation
While we have touched upon other triangulation methods in qualitative research, this article focuses predominantly on researcher triangulation. Therefore, you may benefit from a first-hand example of triangulation in qualitative research for this specific technique.
Consider this example of researcher triangulation. In this hypothetical study, the goal is to conduct research on the effectiveness of novel teaching methods.
Using thematic analysis to study the new teaching method, you use multiple researchers to ensure the credibility and validity of the results. You hire three researchers with different backgrounds to interview students regarding their experiences with the new teaching method.
Researchers receive training sessions and a semi-structured interview guide to follow so that they can interview students in a similar way.
After conducting the interviews, the researchers can meet with the group to discuss what they have noticed and perhaps some patterns they are starting to see.
They can then start doing the first round of coding. Coding separately, they can each develop their own codebook.
Coming together again, they can each discuss their own codebook. Since they coded inductively, their codebooks may be different in many ways. But through comparing and contrasting, they will explore the data rigorously and reflexively. They can then develop a group codebook that they agree on.
Using the group codebook, the researchers can apply this group codebook to the same data (or additional data they haven’t coded yet). They can code the same transcripts (consensus coding) or different transcripts (split coding).
If they applied consensus coding, they can compare if they applied the codes exactly, which is a more direct form of researcher triangulation. Using split coding, they can review each other’s work to understand how their fellow researcher applied the codes.
After this process, much of the work of researcher triangulation will be done, and the researchers will be aligned in their research. The last step of analysis and report writing would be the final step of the process.
Through researcher triangulation, you were able to offer a reliable analysis of the effectiveness of this new teaching method, which other researchers can feel confident citing in their own work.
To avoid confusion, remember two things. First, this is just one example of researcher triangulation, and different steps could certainly be taken. Second, researcher triangulation is not specific to thematic analysis. It can be used in any qualitative research method. In any study that relies heavily on researcher interpretations to generate data, it is particularly valuable.
The Best Tool For Researcher Triangulation
Delve benefits researcher triangulation through real-time communication and coding by multiple researchers. It does this by enhancing collaboration with memo features and offering a web-based collaborative environment that only requires an internet connection.
That means instead of playing email tag or requiring in-person meetings, Delve allows you and your co-researchers to triangulate and discuss your findings from anywhere in the world.
Beyond that, every code and memo is labeled with a timestamp and the name of the researcher who created it. These details organize and streamline the research process even further.
It also makes it easy to invite co-researchers or peer debriefers to collaborate from right within the user interface. With just a few clicks, they’re off and running.
Delve saves you big on time and organizes collaboration—all at an industry-leading price.
Try Delve Qualitative Analysis Tool
The Delve qualitative analysis tool not only improves coder consensus but also centralizes (and organizes) the entire process of researcher triangulation.
Delve is cloud-based, collaborative, and easy to learn. It includes free tutorial videos, responsive customer support, and flexible payment options.
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References
Carter N, Bryant-Lukosius D, DiCenso A, Blythe J, Neville AJ. The use of triangulation in qualitative research. Oncol Nurs Forum. 2014 Sep;41(5):545-7. doi: 10.1188/14.ONF.545-547. PMID: 25158659.
Patton, M. Q. (1999). Enhancing the quality and credibility of qualitative analysis. Health Services Research, 34(5 Pt 2), 1189–1208. https://doi.org/10.1111/1468-0009.00106
Cite This Article
Delve, Ho, L., & Limpaecher, A. (2023c, March 27). What Is Researcher Triangulation in Qualitative Analysis? https://delvetool.com/blog/researcher-triangulation