Research Designs, Triangulation, and Meta-Analysis: Pondering Policy Implications

Research Designs, Triangulation, and Meta-Analysis: Pondering Policy Implications

What are research paradigms? What are research designs? What are research methods? What are the different types of saturation? What are the different types of triangulations? How can meta-analysis be used in triangulation? The answers to these questions are critical to a well-designed study, careful integration, and effective data collection and analysis. In this series on research designs and methods, we will explore these conceptual frameworks, posit some practical guidance, and suggest some best practices.

Research paradigms are philosophical frameworks that shape a good grasp of reality and influence how research is conducted. The main research paradigms include: Positivism (quantitative): Which focuses on objective measurement and statistical analysis, Interpretivism (qualitative): Which emphasizes understanding social phenomena through interpretation and contextual analysis, and Critical Theory (mixed methods): Which seeks to critique and transform social structures and power relationships.

Research design is the overall plan and structure of a research study, including the methods and procedures used to collect and analyze data, such as qualitative, quantitative, and mixed designs.

Research method is the specific technique and tool used to collect and analyze data, such as surveys, experiments, or interviews.

Qualitative design is a research approach that explores non-numerical data, such as text, images, and observations, to gain a deeper understanding of meanings, experiences, and perspectives. It aims to provide rich, contextual, and in-depth insights.

Quantitative design is a research approach that focuses on numerical data, statistical analysis, and experimental designs to test hypotheses and predict outcomes. It aims to provide objective, reliable, and generalizable findings.

Mixed design is a research approach that combines both quantitative and qualitative methods to provide a comprehensive understanding of a research topic. It integrates the strengths of both approaches to address complex research questions.

Validity is the accuracy and truthfulness of research findings, ensuring the study measures what it claims to measure.

Reliability is the consistency and dependability of research findings, ensuring that results are repeatable and stable.

Triangulation involves combining varied and multiple research methods or data sources to increase validity and reliability. Types of triangulations include: Methodological triangulation (combining different research methods), Data triangulation (using multiple data sources from different times, spaces, and people), Investigator triangulation (using multiple researchers in collecting and analyzing data), Theory triangulation (using multiple and varying theoretical perspectives), and Methodological triangulation (using different methodologies to approach the same topic or research questions.

Saturation is the point where no new themes or concepts emerge from the data, indicating comprehensive coverage of the research topic because collecting additional data or analyzing existing data no longer reveals new insights or actionable information. Types of Saturation include:  Data saturation which is when no new themes emerge from additional data collection. Data saturation is the yardstick for assessing and estimating appropriate sample sizes in qualitative studies, Theoretical saturation is when all related theoretical concepts are fully developed and supported, and Analytical saturation is when no new insights emerge from further analysis.

On the other hand, a priori semantic saturation focuses on sampling. Researchers assess the degree to which identified themes or codes are represented in the data. When themes are consistently and unambiguously represented, saturation is achieved. Finally, inductive thematic saturation focuses on both data collection and analysis. Researchers explore the data thoroughly and identify all relevant themes. When new data no longer reveal emerging themes, saturation is achieved.

Some Practice Guidance and Best Practices

- Define clear research questions, and objectives and select appropriate participants and data collection methods (e.g., interviews, focus groups, observations).

- Ensure data quality and saturation (no new themes emerge), and utilize appropriate data analysis techniques (e.g., coding, categorization, theme identification)

- Consider ethical guidelines and informed consent, and clearly define the research questions and inclusion criteria.

- Conduct a comprehensive literature search, and select studies that meet the inclusion criteria, and extract and code data from each study.

- Calculate effect sizes and combine them using statistical methods and interpret the results in the context of the research questions.

- Use purposeful sampling and diverse participants, and ensure data anonymity and confidentiality.

- Use member checking and peer debriefing, and document and report the research process and findings transparently.

- Consider using mixed-methods approaches for comprehensive understanding and utilize a systematic and transparent approach.

- Include a thorough literature search and study selection process and utilize appropriate statistical methods and effect size calculations.

- Interpret results in the context of the research questions and limitations and consider potential biases and limitations.

Meta-analysis can be used as a triangulation method in qualitative studies by combining qualitative and quantitative approaches to increase the validity and reliability of findings. This approach may benefit in various ways:

- Integration of qualitative and quantitative data: Meta-analysis can integrate qualitative data (e.g., themes, codes) with quantitative data (e.g., effect sizes, frequencies) to provide a more comprehensive understanding of the research topic.

-Cross-study analysis: Meta-analysis can be used to analyze data from multiple qualitative studies, identifying patterns and themes across studies, and providing a more generalizable understanding of the research topic.

- Validation of findings: Meta-analysis can validate qualitative findings by quantifying the effect sizes and confidence intervals, providing a more objective measure of the results.

-Comprehensive literature review: Meta-analysis requires a systematic and comprehensive literature review, which can help identify gaps and inconsistencies in the literature and provide a more thorough understanding of the research topic.

-Mixed-methods approach: Meta-analysis can be used in mixed-methods research, combining qualitative and quantitative data to provide a more complete understanding of the research questions or topic.

In sum, the researcher can increase the validity of the study through triangulation. Since each method has its strengths and weaknesses, the study may benefit from skillfully combining complementary methods that mitigate each other’s limitations. The specific approach to saturation may vary depending on the research questions, methodology, and theoretical framework adopted congruent with the relevant extant literature. The researcher should always operationalize saturation and utilize triangulation in ways that align with the goals and context of the study.

Finally, triangulating data, methods, investigators, or theories can mitigate the research bias that comes with using a single perspective in the study. Combining different methods, data sources, and theories enhances the credibility and validity of the study because data reflect real life more closely when gathered using multiple and varied perspectives and techniques. Qualitative research provides rich insights into experiences and meanings, while meta-analysis offers a quantitative summary of existing research. By combining both approaches, the researcher can gain a more comprehensive understanding of the research topic. There is gathering evidence suggesting that meta-analysis is a powerful tool for triangulation in qualitative research, allowing researchers to combine qualitative and quantitative approaches and increase the validity and reliability of their findings.

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Prof James Gaius Ibe is the Chairman/Managing Principal-At Large of the Global Group, LLC-Political Economists and Financial Engineering Consultants, and a senior professor of Economics, Finance, and Marketing Management at one of the local universities. The Global Group, LLC is familiar with the effective use of theoretical and conceptual frameworks. As reflective practitioners, we seek the creative integration of rigorous academic research and industry best practices.