quantitative research design

Focusing on a Research Design Reality: Questions Lead to Answers

Questions Lead to AnswersAt the core of research design development — in quantitative and qualitative methods — is the reality that individuals who have agreed to participate in our research studies generally answer the questions we ask. This fundamental reality places a heavy burden on the researcher developing a quality research design. Survey research that relies on closed-end questionnaire items is vulnerable to unreliable data due to question design that confuses respondents or fosters interpretations outside the true intention of the question asked. All of which leaves the researcher with weak data and consequently flawed analysis and erroneous final results. The need for more involved research designs that effectively investigate complex subject matter is discussed throughout Research Design Review, including in “Life Is Meaningful, Or Is It?: The Road To Meaning In Survey Data” and “Feelings & Sensations: Where Survey Designs Fail Badly.”

Ask a willing research respondent/participant a question and you are likely to get an answer. It may not be the question the researcher intended, it may confuse the responding individual, but the Read Full Text

Shared Constructs in Research Design

Shared constructs

In 2021, a three-part series appeared in Research Design Review concerning three shared constructs in quantitative and qualitative research design — sampling, bias, and validity. Although quantitative and qualitative research, and the respective research designs, are distinct from each other in many ways, there are commonalities across research methodologies that cannot be ignored in quality research design. These commonalities include fundamental constructs that further a principled approach to research design, such as the notion of sampling, bias, and validity.

The three articles posted in 2021 devoted to these shared constructs — Part 1-Sampling, Part 2-Bias, and Part 3-Validity — have been compiled into this single document “Shared Constructs in Research Design,” available for download.

Shared Constructs in Research Design: Part 3 — Validity

validity in research designNot unlike Part 1 (concerning sampling) and Part 2 (concerning bias) of the discussion that began earlier, the shared construct of validity in research design has also been an area of focus in several articles posted in Research Design Review. Most notable is “Quality Frameworks in Qualitative Research” posted in February 2021 in which validity is discussed within the context of the parameters or strategies various researchers use to define and think about the dimensions of rigor in qualitative research design. This article uses the Total Quality Framework (Roller & Lavrakas, 2015) and criteria of Lincoln and Guba (1985) to underscore the idea that quality approaches to design cuts across paradigm orientation, leading to robust and valid interpretations of the data.

Many other qualitative researchers, across disciplines, believe in the critical role that the shared construct of validity plays in research design. Joseph Maxwell, for example, discusses validity in association with his realism approach to causal explanation in qualitative research (Maxwell, 2004); and discusses in detail five unique dimensions of validity, including descriptive validity, interpretative validity, theoretical validity, evaluative validity, and generalizability (Maxwell, 1992). And of course, Miles & Huberman were promoting greater rigor by way of validity more than three decades ago (Miles & Huberman, 1984).

More recently, Koro-Ljungberg (2010) takes an in-depth look at validity in qualitative research and, with extensive literature as the backdrop, makes the case that “validity is in doing, as well as its (un)making, and it exhibits itself in the present paradox of knowing and unknowing, indecision, and border crossing” (p. 609). Matteson & Lincoln (2008) remind educational researchers that validity does not solely concern the analysis phase of research design but “the data collection method must also address validity” (p. 672). Creswell & Miller (2000) discuss different approaches to determine validity across three paradigm orientations — postpositivist, constructivist, and critical — and “lens” of the researcher, participants, and researchers external to the study.

Among qualitative health researchers, Morse (2020) emphasizes the potential weakness in validity when confusing the analysis of interpretative inquiry with that associated with “hard, descriptive data” (p. 4), and Morse et al. (2002) present five verification strategies and argue that validity (as well as reliability) is an “overarching” construct that “can be appropriately used in all scientific paradigms” (p. 19).

These researchers, and those discussed in Part 1 – Sampling and Part 2 – Bias, are admittedly a small share of those who have devoted a great deal of thought and writing concerning these shared constructs. The reader is encouraged to utilize these references to build on their understanding of these constructs in qualitative research and to grow their own library of knowledge.


Creswell, J. W., & Miller, D. L. (2000). Determining validity in qualitative inquiry. Theory into Practice, 39(3), 124–130.

Koro-Ljungberg, M. (2010). Validity, responsibility, and aporia. Qualitative Inquiry, 16(8), 603–610. https://doi.org/10.1177/1077800410374034

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Beverly Hills, CA: Sage Publications.

Matteson, S. M., & Lincoln, Y. S. (2008). Using multiple interviewers in qualitative research studies: The influence of ethic of care behaviors in research interview settings. Qualitative Inquiry, 15(4), 659–674. Retrieved from http://qix.sagepub.com/cgi/doi/10.1177/1077800408330233

Maxwell, J. A. (1992). Understanding and validity in qualitative research. Harvard Educational Review, 62(3), 279–300.

Maxwell, J. A. (2004). Casual explanation, qualitative research, and scientific inquiry in education. Educational Researcher, 33(2), 3–11.

Miles, M. B., & Huberman, A. M. (1984). Drawing valid meaning from qualitative data: Toward a shared craft. Educational Researcher, 13(5), 20–30. https://doi.org/10.3102/0013189X013005020

Morse, J. (2020). The changing face of qualitative inquiry. International Journal for Qualitative Methods, 19, 1–7. https://doi.org/10.1177/1609406920909938

Morse, J. M., Barrett, M., Mayan, M., Olson, K., & Spiers, J. (2002). Verification strategies for establishing reliability and validity in qualitative research. International Journal of Qualitative Methods, 1(2), 13–22.

Roller, M. R., & Lavrakas, P. J. (2015). Applied qualitative research design: A total quality framework approach. New York: Guilford Press.