Was there any evidence of first-person pronoun usage and linguistic indicators of negative emotions that suggest suicidal risk factors?
Could linguistic evidence reveal suicidal ideation prior to his untimely death?
How triangulation is conducted depends on the type of triangulation.
It’s important to remember that triangulation can involve more than one type of triangulation, and this is often the case with mixed-methods research. For example, in mixed-methods research, methodological, investigator and data triangulation may be used to demonstrate the full findings of the research. While Table 28.1 has listed each type separately, examining some of the example papers will show that there is more than one type of triangulation in the studies. Strict adherence to only one triangulation type can make researching the phenomenon more difficult.
Comparing and contrasting theories, data sources, methods and data analyses can ensure strong reliability and validity in research results. However, this can also be time-consuming and resource-intensive. Attention needs to be paid to the nuances of the research, to provide holistic explanations. There are times when triangulation may not be considered necessary, and this also needs to be understood when addressing the research question. For example, if the purpose of the research is to develop a new theory, there may be no need to include more than one method, data point or theoretical foundation.
Triangulation is the use of more than one data source, investigator, theory or method in the same research. There are four main triangulation types: each provides a means for examining the research from different perspectives and for ensuring the rigour, validity and credibility of findings.
Qualitative Research – a practical guide for health and social care researchers and practitioners Copyright © 2023 by Tess Tsindos is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.
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Triangulation refers to the use of multiple methods or data sources in qualitative research to develop a comprehensive understanding of phenomena (Patton, 1999). Triangulation also has been viewed as a qualitative research strategy to test validity through the convergence of information from different sources. Denzin (1978) and Patton (1999) identified four types of triangulation: (a) method triangulation, (b) investigator triangulation, (c) theory triangulation, and (d) data source triangulation. The current article will present the four types of triangulation followed by a discussion of the use of focus groups (FGs) and in-depth individual (IDI) interviews as an example of data source triangulation in qualitative inquiry.
Keywords: focus groups; in-depth individual interviews; qualitative research; triangulation.
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Published on 8 April 2022 by Pritha Bhandari . Revised on 16 January 2023.
Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question . It’s a research strategy that can help you enhance the validity and credibility of your findings.
Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . If you decide on mixed methods research , you’ll always use methodological triangulation.
Types of triangulation in research, what is the purpose of triangulation, pros and cons of triangulation in research, frequently asked questions about triangulation.
There are four main types of triangulation:
We’ll walk you through the four types of triangulation using an example. This example is based on a real study .
When you use methodological triangulation, you use different methods to approach the same research question.
This is the most common type of triangulation, and researchers often combine qualitative and quantitative research methods in a single study.
Methodological triangulation is useful because you avoid the flaws and research bias that come with reliance on a single research technique.
In data triangulation, you use multiple data sources to answer your research question. You can vary your data collection across time, space, or different people.
When you collect data from different samples, places, or times, your results are more likely to be generalisable to other situations.
With investigator triangulation, you involve multiple observers or researchers to collect, process, or analyse data separately.
Investigator triangulation helps you reduce the risk of observer bias and other experimenter biases.
Triangulating theory means applying several different theoretical frameworks in your research instead of approaching a research question from just one theoretical perspective.
Testing competing hypotheses is one way to perform theory triangulation. Using theory triangulation may help you understand a research problem from different perspectives or reconcile contradictions in your data.
Researchers use triangulation for a more holistic perspective on a specific research question. Triangulation is also helpful for enhancing credibility and validity.
It’s important to gather high-quality data for rigorous research. When you have data from only one source or investigator, it may be difficult to say whether the data are trustworthy.
But if data from multiple sources or investigators line up, you can be more certain of their credibility.
Credibility is about how confident you can be that your findings reflect reality. The more your data converge, or or agree with each other, the more credible your results will be.
Triangulation helps you get a more complete understanding of your research problem.
When you rely on only one data source, methodology, or investigator, you may risk bias in your research. Observer bias may occur when there’s only one researcher collecting data. Similarly, using just one methodology means you may be disadvantaged by the inherent flaws and limitations of that method.
It’s helpful to use triangulation when you want to capture the complexity of real-world phenomena. By varying your data sources, theories, and methodologies, you gain insights into the research problem from multiple perspectives and levels.
Validity is about how accurately a method measures what it’s supposed to measure.
You can increase the validity of your research through triangulation. Since each method has its own strengths and weaknesses, you can combine complementary methods that account for each other’s limitations.
Finally, fMRI data can tell you more about hidden neural mechanisms without any participant interference. But this type of data is only valuable for your research when combined with the others.
Like all research strategies, triangulation has both advantages and disadvantages.
Triangulating data, methods, investigators, or theories helps you avoid the bias that comes with using a single perspective in your research. You’ll get a well-rounded look into the research topic when you use triangulation.
Combining different methods, data sources, and theories enhances the credibility and validity of your research. You’ll be able to trust that your data reflect real life more closely when you gather them using multiple perspectives and techniques.
Triangulation can be very time-consuming and labour-intensive. You’ll need to juggle different datasets, sources, and methodologies to answer one research question.
This type of research often involves an interdisciplinary team and a higher cost and workload. You’ll need to weigh your options and strike a balance based on your time frame and research needs.
Sometimes, the data from different sources, investigators, methods may not line up to give you a clear picture. Your data may be inconsistent or contradict each other.
This doesn’t necessarily mean that your research is incoherent. Rather, you’ll need to dig deeper to make sense of why your data are contradictory. These inconsistencies can be challenging but may also lead to new avenues for further research.
Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.
Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.
There are four main types of triangulation :
Triangulation can help:
But triangulation can also pose problems:
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The Use of Triangulation in Qualitative Research
Nancy Carter
Denise Bryant-Lukosius
Alba DiCenso
Jennifer Blythe
Alan J. Neville
Triangulation refers to the use of multiple methods or data sources in qualitative research to develop a comprehensive understanding of phenomena (Patton, 1999). Triangulation also has been viewed as a qualitative research strategy to test validity through the convergence of information from different sources. Denzin (1978) and Patton (1999) identified four types of triangulation: (a) method triangulation, (b) investigator triangulation, (c) theory triangulation, and (d) data source triangulation. The current article will present the four types of triangulation followed by a discussion of the use of focus groups (FGs) and in-depth individual (IDI) interviews as an example of data source triangulation in qualitative inquiry.
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Systematic reviews, case study research methodology in nursing research, preferred reporting items for systematic reviews and meta-analyses.
Triangulating data in research involves combining multiple sources, methods, or perspectives to ensure the credibility, validity, and reliability of findings. Here's a step-by-step guide on how to triangulate data in research:
Let's say you and your insights team are looking for the answer to the question, "How do Pros shop for tools at home improvement retailers?"
To comprehensively understand the answer to this question in a data-driven way, you and your team would want to deploy strategic triangulation approaches.
Triangulation in qualitative research refers to the practice of using multiple sources, methods, data types, researchers, theories, or perspectives to investigate a research question. The goal of triangulation is to enhance the credibility, validity, and reliability of findings by reducing bias, increasing the richness of data, and ensuring that the results are robust and well-supported.
There are several forms of triangulation that researchers can employ in qualitative research:
This involves using multiple sources of data to examine the same phenomenon. For example, a researcher might gather information from interviews, observations, and documents to gain a comprehensive understanding of a topic.
This refers to using multiple research methods to study the same research question. For instance, combining interviews with shopping homework exercises can provide a more comprehensive view of a situation.
In this form, multiple researchers or observers are involved in the research process. Each researcher might bring different perspectives, biases, and interpretations to the data, leading to a more well-rounded understanding of the topic.
This involves using multiple theoretical frameworks to analyze the data. By approaching the data from different theoretical perspectives, researchers can gain deeper insights and uncover nuances that might otherwise be overlooked.
This refers to studying the same phenomenon at different points in time. Comparing data collected at different time periods can reveal changes, trends, and developments over time.
The idea behind triangulation is that by combining various sources of evidence and perspectives, researchers can cross-validate their findings and mitigate the limitations inherent in any single approach. This enhances the credibility of the research and increases confidence in the interpretations drawn from the data. However, it's important to note that triangulation does not eliminate all potential biases or errors, but it does provide a more comprehensive and reliable view of the research topic.
Research question:.
Back to the original example of a research question to be answered: "How do Pros shop for tools at home improvement retailers?"
To comprehensively understand the answer to this question in a data-driven way, you and your team would want to deploy the following triangulation approaches:
Data Triangulation: Collect data from multiple sources. Conduct in-depth interviews with Pros, analyze their written and video reflections on a shopping assignment at specific retailers, and gather and analyze the purchase data from the retailer.
Methodological Triangulation: Use multiple research methods. Alongside interviews, administer a survey to a larger sample of Pros to quantitatively measure their purchasing behavior using the data compiled in qualitative to create the survey. This allows for a comparison between qualitative insights and quantitative trends.
Investigator Triangulation: Involve multiple researchers. Have different researchers analyze the interview transcripts independently and then come together to compare and discuss their interpretations, reducing the impact of individual biases.
Theory Triangulation: Apply different theoretical lenses. Analyze the data using theories from retailer client knowledge base, data trends and industry data to gain various perspectives on the Pro’s experiences.
Time Triangulation: Study changes among the audience segment over time. Conduct interviews and data collection at different points to capture how Pros' experiences and perceptions of the tool purchasing experience have changed or stayed constant. View the latest data from the Pro Monthly Tracker >>
By employing these forms of triangulation, the qualitative research findings will be more comprehensive and reliable. The insights from different data sources, methods, researchers, theories, and time periods will converge to provide a deeper understanding of how Pros shop for tools. This multi-faceted approach helps to confirm and enrich the interpretations drawn from the data.
1. define your research question:.
Before doing anything else, you and your insights team must clearly articulate your research question or topic of interest. This will guide the rest of the triangulation process. Read more about 7 Mistakes to Avoid When Conducting Qualitative Research Internally >>
Choose different sources of data that can provide insights into your research question. These sources could include interviews, observations, surveys, documents, audiovisual materials, and more. Read more about How to Choose the Best Survey Method That Will Help You Get Results >>
Collect data from each chosen source. Ensure that the data collection methods are appropriate for the type of data you're gathering and the research question you're exploring.
Analyze the data from each source independently. This could involve coding, categorizing, or otherwise organizing the data to identify themes, patterns, and trends.
Compare the findings from each data source. Look for areas where the data sources converge, meaning that they provide similar insights or evidence. Also, pay attention to any divergences, where the data sources present differing perspectives or findings.
Combine the findings from different data sources. This can involve creating a comprehensive synthesis of the data that highlights the key themes and patterns across sources. Address how the convergent and divergent findings contribute to a more nuanced understanding of the research question.
Reflect on the process of triangulation itself. Consider the strengths and limitations of each data source, method, or perspective. Discuss how the different sources of data complement or enrich each other.
Ensure that the interpretations and conclusions drawn from the triangulated data are consistent and coherent. This reinforces the credibility of the findings.
Clearly document the process of triangulation in your research report. Describe the data sources, methods, and strategies used to integrate findings. This transparency helps other researchers assess the rigor of your approach.
Discuss the implications of the triangulated findings. Explain how the combination of multiple data sources or perspectives has influenced the depth and breadth of your understanding of the research question.
Triangulating data requires careful planning, execution, and analysis. It's a dynamic process that enhances the validity and reliability of qualitative research by drawing on multiple sources of evidence. The goal of your research project is to present a more comprehensive and nuanced perspective on the research topic.
Delivering actionable insights through this process is what our market intelligence team at The Farnsworth Group remains focused on, exclusively for building product manufacturers, retailers, and industry stakeholders, just as we have for roughly 35 years.
Using the most appropriate qualitative and quantitative research methodologies and modeling to answer the question(s) at hand, we provide recommendations on what your customers are looking for, so that you can be most successful in your specific market.
Simply schedule a consultation to learn more about the answers you would be able to get to your specific customer, product, and market related questions.
Learn more about the various custom market research services you can pursue with our team as well:
Home » Triangulation in Research – Types, Methods and Guide
Table of Contents
Definition:
Triangulation is a research technique that involves the use of multiple methods or sources of data to increase the validity and reliability of findings.
When triangulated, data from different sources can be combined and analyzed to produce a more accurate understanding of the phenomenon being studied. Triangulation can be used in both quantitative and qualitative research and can be implemented at any stage of the research process.
There are many types of Triangulation in research but we are featuring only Five main types:
Data triangulation is the use of multiple sources of data to examine a research question or phenomenon. This can include using a variety of data collection methods, such as surveys, interviews, observations, and document analysis, to gain a more comprehensive understanding of the phenomenon. By using multiple sources of data, researchers can validate their findings and reduce the risk of bias that may occur when using a single method.
Methodological triangulation involves using multiple research methods to investigate a research question or phenomenon. This can include both qualitative and quantitative methods, or different types of qualitative methods, such as focus groups and interviews. By using multiple methods, researchers can strengthen their findings, as well as gain a more comprehensive understanding of the phenomenon.
Theoretical triangulation involves using multiple theoretical frameworks or perspectives to analyze and interpret research findings. This can include applying different theoretical models or approaches to the same data to gain a deeper understanding of the phenomenon. The use of multiple theories can also help to validate findings and identify inconsistencies.
Investigator triangulation involves using multiple researchers to examine a research question or phenomenon. This can include researchers with different backgrounds, expertise, and perspectives, to reduce the risk of bias and increase the validity of the findings. It can also help to validate the findings by having multiple researchers analyze and interpret the data.
Time triangulation involves studying the same phenomenon or research question at different time points. This can include longitudinal studies that track changes over time, or retrospective studies that examine the same phenomenon at different points in the past. Time triangulation can help to identify changes or patterns in the phenomenon, as well as validate findings over time.
Triangulation is a research technique that involves using multiple methods, sources, or perspectives to validate or corroborate research findings. Here are some common triangulation methods used in research:
Triangulating between qualitative and quantitative methods involves using both types of research methods to collect data and analyze the phenomenon under investigation. This can help to strengthen the validity and reliability of the findings by providing a more comprehensive understanding of the phenomenon.
Triangulating between multiple data sources involves collecting data from various sources to validate the findings. This can include using data from interviews, observations, surveys, or archival records to corroborate the findings.
Triangulating between multiple researchers involves using multiple researchers to analyze and interpret the data. This can help to ensure the findings are not biased by the perspectives of a single researcher.
Triangulating between theories involves using multiple theoretical frameworks to analyze and interpret the data. This can help to identify inconsistencies in the findings and provide a more comprehensive understanding of the phenomenon under investigation.
Triangulating between methodologies involves using multiple research methods within a single research design. For example, a study may use both qualitative and quantitative methods to investigate the same phenomenon, providing a more comprehensive understanding of the phenomenon.
Triangulating between time involves studying the same phenomenon at different points in time. This can help to identify changes in the phenomenon over time and validate the findings across time.
Triangulating between participants involves collecting data from multiple participants with different backgrounds, experiences, or perspectives. This can help to validate the findings and provide a more comprehensive understanding of the phenomenon under investigation.
Here are some common triangulation data collection methods used in research:
Interviews are a popular data collection method used in qualitative research. Researchers may use different types of interviews, such as structured, semi-structured, or unstructured interviews, to gather data from participants. Triangulating interviews involves conducting multiple interviews with different participants or conducting interviews with the same participants at different times to validate or corroborate the findings.
Observations involve systematically observing and recording behavior or interactions in a natural setting. Researchers may use different types of observations, such as participant observation, non-participant observation, or structured observation, to collect data. Triangulating observations involves collecting data from different observers or conducting observations at different times to validate or corroborate the findings.
Surveys involve collecting data from a large number of participants using standardized questionnaires. Researchers may use different types of surveys, such as self-administered surveys or telephone surveys, to collect data. Triangulating surveys involves collecting data from different surveys or using surveys in combination with other data collection methods to validate or corroborate the findings.
Document analysis involves systematically analyzing and interpreting documents, such as government reports, policy documents, or archival records, to understand a phenomenon. Triangulating document analysis involves analyzing different types of documents or using document analysis in combination with other data collection methods to validate or corroborate the findings.
Focus groups involve bringing together a group of people to discuss a specific topic or phenomenon. Researchers may use different types of focus groups, such as traditional focus groups or online focus groups, to collect data. Triangulating focus groups involves conducting multiple focus groups with different participants or conducting focus groups in combination with other data collection methods to validate or corroborate the findings.
Here are some common data analysis methods used in triangulation:
Here are some general steps to conduct triangulation in research:
Here are some common applications of triangulation:
Here are some real-time examples of triangulation:
The purpose of triangulation in research is to increase the validity and reliability of the findings by using multiple data sources and methods to study the same phenomenon. Triangulation can help to mitigate the limitations of using a single data source or method and can provide a more comprehensive understanding of the research question or objective.
By using multiple data sources and methods, triangulation can help to:
Here are some situations where triangulation may be appropriate:
Here are some advantages of using triangulation:
Here are some limitations of using triangulation:
Researcher, Academic Writer, Web developer
Qualitative methods are sometimes criticised as being subjective, based on single, unreliable sources of data. But with the exception of some case study research, most qualitative research will be designed to integrate insights from a variety of data sources
Triangles are my favourite shape, Three points where two lines meet alt-J
Qualitative methods are sometimes criticised as being subjective, based on single, unreliable sources of data. But with the exception of some case study research, most qualitative research will be designed to integrate insights from a variety of data sources, methods and interpretations to build a deep picture. Triangulation is the term used to describe this comparison and meshing of different data, be it combining quantitative with qualitative, or ‘qual on qual’.
I don’t think of a data in qualitative research as being a static and definite thing. It’s not like a point of data on a plot of graph: qualitative data has more depth and context than that. In triangulation, we think of two points of data that move towards an intersection. In fact, if you are trying to visualise triangulation, consider instead two vectors – directions suggested by two sources of data, that may converge at some point, creating a triangle. This point of intersection is where the researcher has seen a connection between the inference of the world implied by two different sources of data. However, there may be angles that run parallel, or divergent directions that will never cross: not all data will agree and connect, and it’s important to note this too.
You can triangulate almost all the constituent parts of the research process: method, theory, data and investigator.
Data triangulation, (also called participant or source triangulation) is probably the most common, where you try to examine data from different respondents but collected using the same method. If we consider that each participant has a unique and valid world view, the researcher’s job is often to try and look for a pattern or contradictions beyond the individual experience. You might also consider the need to triangulate between data collected at different times, to show changes in lived experience.
Since every method has weaknesses or bias, it is common for qualitative research projects to collect data in a variety of different ways to build up a better picture. Thus a project can collect data from the same or different participants using different methods, and use method or between-method triangulation to integrate them. Some qualitative techniques can be very complementary, for example semi-structured interviews can be combined with participant diaries or focus groups, to provide different levels of detail and voice. For example, what people share in a group discussion maybe less private than what they would reveal in a one-to-one interview, but in a group dynamic people can be reminded of issues they might forget to talk about otherwise.
Researchers can also design a mixed-method qualitative and quantitative study where very different methods are triangulated. This may take the form of a quantitative survey, where people rank an experience or service, combined with a qualitative focus group, interview or even open-ended comments. It’s also common to see a validated measure from psychology used to give a metric to something like pain, anxiety or depression , and then combine this with detailed data from a qualitative interview with that person.
In ‘theoretical triangulation’, a variety of different theories are used to interpret the data, such as discourse, narrative and context analysis, and these different ways of dissecting and illuminating the data are compared.
Finally there is ‘investigator triangulation’, where different researchers each conduct separate analysis of the data, and their different interpretations are reconciled or compared. In participatory analysis it’s also possible to have a kind of respondent triangulation, where a researcher is trying to compare their own interpretations of data with that of their respondents.
While there is a lot written about the theory of triangulation, there is not as much about actually doing it ( Jick 1979 ). In practice, researchers often find it very difficult to DO the triangulation: different data sources tend to be difficult to mesh together, and will have very different discourses and interpretations. If you are seeing ‘anger’ and ‘dissatisfaction’ in interviews with a mental health service, it will be difficult to triangulate such emotions with the formal language of a policy document on service delivery.
In general the qualitative literature cautions against seeing triangulation as a way to improve the validity and reliability of research, since this tends to imply a rather positivist agenda in which there is an absolute truth which triangulation gets us closer to. However, there are plenty that suggest that the quality of qualitative research can be improved in this way, such as Golafshani (2003) . So you need to be clear of your own theoretical underpinning: can you get to an ‘absolute’ or ‘relative’ truth through your own interpretations of two types of data? Perhaps rather than positivist this is a pluralist approach, creating multiplicities of understandings while still allowing for comparison.
It’s worth bearing in mind that triangulation and multiple methods isn’t an easy way to make better research. You still need to do all different sources justice: make sure data from each method is being fully analysed, and iteratively coded (if appropriate). You should also keep going back and forth, analysing data from alternate methods in a loop to make sure they are well integrated and considered.
Qualitative data analysis software can help with all this, since you will have a lot of data to process in different and complementary ways. In software like Quirkos you can create levels, groups and clusters to keep different analysis stages together, and have quick ways to do sub-set analysis on data from just one method. Check out the features overview or mixed-method analysis with Quirkos for more information about how qualitative research software can help manage triangulation.
References and further reading
Carter et al. 2014, The use of triangulation in qualitative research, Oncology Nursing Forum, 41(5), https://www.ncbi.nlm.nih.gov/pubmed/25158659
Denzin, 1978 The Research Act: A Theoretical Introduction to Sociological Methods, McGraw-Hill, New York.
Golafshani, N., 2003, Understanding reliability and validity in qualitative research, 8(4), https://nsuworks.nova.edu/cgi/viewcontent.cgi?article=1870&context=tqr
Bekhet A, Zauszniewski J, 2012, Methodological triangulation: an approach to understanding data, Nurse Researcher, 20 (2), https://journals.rcni.com/doi/pdfplus/10.7748/nr2012.11.20.2.40.c9442
Jick, 1979, Mixing Qualitative and Quantitative Methods: Triangulation in Action, Administrative Science Quarterly, 24(4), https://www.jstor.org/stable/2392366
Please note you do not have access to teaching notes, using triangulation to validate themes in qualitative studies.
Qualitative Research in Organizations and Management
ISSN : 1746-5648
Article publication date: 21 August 2009
The purpose of this paper is to provide instructional guidance on how to increase validity and reduce subjectivity in qualitative studies, such as grounded theory. The paper also demonstrates how different techniques can help management research by including informants/managers in a time efficient way.
This paper describes how three complementary triangulation methods can be used for validation and exploration of concepts and themes in qualitative studies. Tree graphs, concept mapping, and member checking are applied in a managerial case study, complementing a conventional grounded theory approach.
The paper suggests that naturalistic inquiries, such as grounded theory and thematic analysis, can use mixed methods and multiple sources and coders in order to offset biases and to validate and sort findings. The case study presents three different perspectives on how an organization comprehends diversity as a strategic issue.
The paper suggests a mixed methods design that addresses some of the potential shortcomings often found in grounded theory and other qualitative studies, their theory development and their documentation of processes. It positions the approach over the range of the triangulation literature and it argues that it is important to be aware of different triangulation mindsets, and these they are not necessarily contradictory.
Jonsen, K. and Jehn, K.A. (2009), "Using triangulation to validate themes in qualitative studies", Qualitative Research in Organizations and Management , Vol. 4 No. 2, pp. 123-150. https://doi.org/10.1108/17465640910978391
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> > - checking out the consistency of findings generated by different data collection methods. - examining the consistency of different data sources from within the same method. For example: - using multiple analyst to review findings or using multiple observers and analysts to seek consensus, but to understand multiple ways of seeing the data - using multiple theoretical perspectives to examine and interpret the data . 10(3) pp. 378-395. . Thousand Oaks, CA: Sage Publications. . New York: McGraw-Hill. . Newbury Park, CA: Sage Publications. . 320(7226), 50-52. . 34 (5) Part II. pp. 1189-1208. (2nd Edition). Thousand oaks, CA: Sage Publications. |
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TRIANGULATION IN SOCIAL RESEARCH
Academia Letters
Anita Bans-Akutey
Benjamin Tiimub , Anita Bans-Akutey
Research triangulation, over the years, has gained much popularity as researchers become more sophisticated in generating and testing theories. Indeed of what use is research whose findings are unreliable and invalid? Answers to research questions are expected to be as close as they possibly can to the reality if they cannot be perfectly accurate. Researchers find a way of producing reliable results by making use of research triangulation. This paper seeks to identify advantages that come with a researcher making use of research triangulation in a study. According to Noble and Heale (2019), research triangulation refers to the process that helps to increase the credibility and validity of research. In other words, research triangulation basically aims at validating the results of a study. Triangulation, sometimes, makes use of mixed methods to achieve the aim of validating research findings. However, triangulation is not the same as mixed methods. Mixed methods basically combine quantitative and qualitative research approaches in getting research questions answered; while triangulation describes how the researcher makes use of all the multiple approaches in the study to extract the required information as well as critically analysing findings (Social Sciences Research Laboratories, 2018); thus establishing validity and credibility. Validity in research basically establishes how correctly a particular approach measures something and how closely findings are to actual values or concepts being examined (Noble & Heale, 2019). It indicates whether findings from a particular research can be trusted. Achieving validity is very important to ensure that findings from a research can be correctly used and interpreted in such a way that stakeholders of the study are able to make informed
Oncology Nursing Forum
Jennifer Blythe
Administrative science quarterly
Gemma Nicholls
Quality & Quantity
Norman Blaikie
Explorations in methodology
Alexander Massey
A number of philosophical assumptions within the original conception of triangulation (as practised in land surveying etc.) simply do not translate into the field of multiple methods research in the social sciences. At least seven types of logical error have been identified in the practices which can be generally grouped under the designation of methodological triangulation. In addition, the goal of completeness bears little or no relation to the original concept of triangulation. Because qualitative social sciences have misappropriated the term 'triangulation', many false and misleading conclusions are drawn within mainstream and otherwise respected pieces of research. Headings include: common error types in methodological triangulation; appropriation of triangulation by the social sciences; the spectre of positivism; the logical fallacy of mutual confirmation; the myths of convergence, divergence, and bias; how to be lost without even knowing it (a recent example); the illusory goal of 'completeness' First published in Massey, A. and Walford, G. (Eds.) (1999) Explorations in methodology, Studies in Educational Ethnography, Vol.2, Stamford, JAI Press, 183-197
Rashi Mishra
Triangulation involves using multiple data sources in an investigation to produce understanding. Triangulation in sociological research is the use of three or more contrasting methods in a study to produce three different sets or even types of data. Its purpose is to reduce the weight given to any individual set of results. 'Triangulation' can also be achieved by using different research techniques. Triangulated techniques are helpful for cross-checking and used to provide confirmation and completeness, which brings 'balance' between two or more different types of research. The purpose is to increase the credibility and validity of the results. Often this purpose in specific contexts is to obtain confirmation of findings through convergence of different perspectives. There are various types of triangulation which can be done at various stage of the research. It has got lot of relevance in case study as it is believed that its lacks in objectivity.Case studies has various advantages, in that they present data of real-life situations and they provide better insights into the detailed behaviors of the subjects of interest, they are also criticized for their inability to generalize their results. Thus triangulation can help to overcome its disadvantages. It helps to increase its construct validity
Tshidi M Wyllie
Tshidi M Wyllie,Ph.D.
There controversies surrounding Triangulation as an approach to research, despite the controversial debates that have been ongoing for decades pertaining to the qualitative-quantitative dichotomy; multi-method and/or mixed method or triangulation as some researchers choose to call it. The debate mostly surround the issue of whether or not to triangulate research methods, data, strategies and/or approaches. As long as learning is a continued process and evolves with time, and is as diverse as are researchers and scholars in different fields of study, the debate is bound to equally become complex and possibly still continue. However, this paper however chooses not to pursue the controversies but rather to focus on the power and/or the benefits of triangulation.
Geofrey Lusaggi
Research triangulation is a paramount approach that has indisputable advantages in the struggle of producing valid, reliable, balanced, and generalizable research results. Thurmond (2001) puts it right that “Many researchers strive to design studies that will not only give a multidimensional perspective of the phenomenon but will also provide rich, unbiased data that can be interpreted with a comfortable degree of assurance”, here credit and gratitude goes to research triangulation approach. However, the research must be aware of where, how and when to apply certain research method mixes and their respective limitations should be identified and addressed for better results.
Remco Heesen , Liam Kofi Bright
Social scientists use many different methods, and there are often substantial disagreements about which method is appropriate for a given research question. In response to this uncertainty about the relative merits of different methods, W. E. B. Du Bois advocated for and applied `methodological triangulation'. This is to use multiple methods simultaneously in the belief that, where one is uncertain about the reliability of any given method, if multiple methods yield the same answer that answer is confirmed more strongly than it could have been by any single method. Against this, methodological purists believe that one should choose a single appropriate method and stick with it. Using tools from voting theory, we show Du Boisian methodological triangulation to be more likely to yield the correct answer than purism, assuming the scientist is subject to some degree of diffidence about the relative merits of the various methods. This holds even when in fact only one of the methods is appropriate for the given research question.
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UNICAF University - Zambia
Ivan Steenkamp
Khan F Rahman
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David Morgan
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Olutoye Olutayo
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Susan Turner
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In this chapter, we will learn about two groups of data collection techniques: custom-data and existing-data collection. Then we will delve into the details of popular collection techniques such as pre-interview questionnaires, semi-structured interviews, and observations. We will look into other sources and collection techniques such as focus groups, surveys, recordings, texts, social media, artefacts, data mining, and immersive experiences in extended realities. Researchers will benefit from reading this chapter in conjunction with the Basics of Qualitative Data Collection , Qualitative Data Preparation and Filtering , and Socio-technical Grounded Theory for Qualitative Data Analysis chapters. Collectively, they cover socio-technical grounded theory’s Basic Stage.
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Hoda, R. (2024). Techniques of Qualitative Data Collection. In: Qualitative Research with Socio-Technical Grounded Theory. Springer, Cham. https://doi.org/10.1007/978-3-031-60533-8_8
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Examples: Triangulation in different types of research. Qualitative research: You conduct in-depth interviews with different groups of stakeholders, such as parents, teachers, and children. Quantitative research: You run an eye-tracking experiment and involve three researchers in analyzing the data. Mixed methods research: You conduct a ...
In qualitative research, triangulation is the method that helps researchers build a strong case for their findings. Just like a detective who gathers evidence from multiple sources to solve a complex mystery, a researcher using triangulation draws upon various data points, methods, and perspectives to paint a more complete picture of the topic ...
For Cowman, triangulation is defined as the combination of multiple methods in studying the same object or event to better address the phenomenon researched. In turn, Morse defines as the use of at least two methods, usually qualitative and quantitative, to guide the same research problem. When a singular research method is inadequate ...
Triangulation is a method used to increase the credibility and validity of research findings.1 Credibility refers to trustworthiness and how believable a study is; validity is concerned with the extent to which a study accurately reflects or evaluates the concept or ideas being investigated.2 Triangulation, by combining theories, methods or observers in a research study, can help ensure that ...
Using quantitative and qualitative methods together enables the research to answer the questions of 'what' and 'why' (see Chapter 11: Mixed Methods). The BroSupPort portal study 3 is a good example of methodological triangulation because it used a combination of workshops, interviews and focus groups to collect data.
Abstract. Triangulation refers to the use of multiple methods or data sources in qualitative research to develop a comprehensive understanding of phenomena (Patton, 1999). Triangulation also has been viewed as a qualitative research strategy to test validity through the convergence of information from different sources.
Deacon D., Bryman A., Fenton N. (1998). Collision or collusion? A discussion and case study of the unplanned triangulation of quantitative and qualitative research methods. International Journal of Social Research Methodology, 1, 47-63.
Examples: Triangulation in different types of research. Qualitative research: You conduct in-depth interviews with different groups of stakeholders, such as parents, teachers, and children. Quantitative research: You run an eye-tracking experiment and involve three researchers in analysing the data. Mixed methods research: You conduct a ...
the sense that research findings are supported by the evidence. Triangulation is a method used by qualita-tive researchers to check and establish validity in their stud. es by analyzing a research question from multiple perspectives. Patton (2002) cautions that it is a common misconception that the goal of triangulation is to arrive at ...
Preview. Triangulation refers to the use of multiple methods or data sources in qualitative research to develop a comprehensive understanding of phenomena (Patton, 1999). Triangulation also has been viewed as a qualitative research strategy to test validity through the convergence of information from different sources.
The study examines the concept of the "triangulation approach" in the social research methodology. Triangulation is an innovative method, particularly in qualitative and multi-method research ...
Triangulation in qualitative research refers to the practice of using multiple sources, methods, data types, researchers, theories, or perspectives to investigate a research question. The goal of triangulation is to enhance the credibility, validity, and reliability of findings by reducing bias, increasing the richness of data, and ensuring ...
This research is a qualitative research using triangulation analysis based on 3 sources of data which are past literatures, regulations and interviews. ... Qualitative research methods can reveal ...
Here are some real-time examples of triangulation: Mixed-methods research: Mixed-methods research is a common example of triangulation that involves using both quantitative and qualitative research methods to collect and analyze data. This approach can help to validate or corroborate the findings by providing multiple perspectives on the same ...
The use of triangulation in qualitative studies employing elite interviews. Developing and Implementing a Triangulation Protocol for Qualitative Health Research. The Concepts of Qualitative Data: Challenges in Neoliberal Times for Qualitative Inquiry. Triangulation, Respondent Validation, and Democratic Participation in Mixed Methods Research.
Triangulation is a research methods strategy that uses multiple data sources, researchers, theories, or research methods to ensure that the data, analysis, and conclusions of a research study are as comprehensive and accurate as possible. ... Triangulation in qualitative research establishes legitimation, particularly credibility, in ...
Doing Triangulation and Mixed Methods. This book shows you not just how to use triangulation as a strategy of quality management, but also how to use it as an approach to designing and doing qualitative research in a more comprehensive way. Flick links triangulation with current debates about using mixed methods, and outlines their potential ...
Methodological triangulation is the most common type of triangulation.2 Studies that use triangulation may include two or more sets of data collection using the same methodology, such as from qualitative data sources. Alternatively, the study may use two different data collection methods as with qualitative and quantitative.4 "This can allow the limitations from each method to be transcended ...
Qualitative methods are sometimes criticised as being subjective, based on single, unreliable sources of data. But with the exception of some case study research, most qualitative research will be designed to integrate insights from a variety of data sources ... Carter et al. 2014, The use of triangulation in qualitative research, Oncology ...
Design/methodology/approach. This paper describes how three complementary triangulation methods can be used for validation and exploration of concepts and themes in qualitative studies. Tree graphs, concept mapping, and member checking are applied in a managerial case study, complementing a conventional grounded theory approach.
Regarding reliability, triangulation methods were used for both data and researchers. Qualitative data obtained through open-ended interviews were contrasted with an analysis of the co-occurrence of terms in a database of 6081 studies imported from Scopus, which allowed corroboration of emerging findings from multiple sources of evidence.
Definition. Triangulation involves using multiple data sources in an investigation to produce understanding. Some see triangulation as a method for corroborating findings and as a test for validity. This, however, is controversial. This assumes that a weakness in one method will be compensated for by another method, and that it is always ...
What is triangulation. Triangulation is a method used to increase the cred-ibility and validity of research findings.1 Credibility refers to trustworthiness and how believable a study is; validity is concerned with the extent to which a study accurately reflects or evaluates the concept or ideas being investigated.2 Triangulation, by combining ...
Finally, the use of triangulation leads to a synthesis or integration of theories. In this sense, it is methodological triangulation, i.e. to bring diverse theories to bear on a common problem. A thread linking all the above-mentioned benefits is the important part played by the qualitative research method in triangulation.
Qualitative Research, 10(3), 357-376. Article Google Scholar O'Connor, R. (2012). Using grounded theory coding mechanisms to analyze case study and focus group data in the context of software process research.
Methods and analysis: We will use the socioecological framework and employ a concurrent triangulation, mixed-methods study design to achieve three specific aims: (1) examine the impacts of the ...
Since 2015, he has been an adjunct professor of family medicine at the University of Michigan and co-director of the Michigan Mixed Methods Research and Scholarship Program. He was formerly a professor of educational psychology at the University of Nebraska-Lincoln, where he held the Clifton Endowed Professor Chair.He was a founding co-editor of the Journal of Mixed Methods Research, and was ...