Common Analytical Approaches

There is a wide range of interpretive or analytical approaches employed in qualitative research.  Here, we briefly describe a few interpretive approaches commonly used in health research:

Content Analysis

Narrative Analysis

The Constant Comparative Method of Grounded Theory

Approaches to the Analysis of Interaction between Providers and Patients

Because of the diversity in analytical approaches that can be employed in qualitative research, when preparing a report or manuscript it is useful to:

  • Avoid jargon
  • Assume your readers are unfamiliar with the analytical approach you employed and describe, in adequate detail, what you did (for more see audit trail

While interpretive approaches have unique features, the growing literature describing 'how to do' qualitative analysis highlights some common features of qualitative analysis.  These include:

Data managment issues and techniques

Iterative sampling/analysis

Coding text


Displaying data

Designing and Analyzing Multimethod data

If is fairly common in healthcare research to find study designs that merge qualitative and quantitative data.  Below we provide several resources that discuss how to conduct studies that use multiple methods.  Here, we overview a few key points.

  • There are several strategies and reasons for linking qualitative and quantitative methods, and several authors articulate strategies for linking qualitative and quantitative methods in a complementary fashion (c.f. Miles and Huberman, 1994; Greene et al, 1989; Morgan, 1998; Sandelowski, 1995; Rossman & Wilson, 1985 and 1994; and Patton, 2002).

Miller and Crabtree (1994) highlight 4 broad approaches:

    • Concurrent design - two independent studies are conducted on the same study population and the results are converged.  For example, interventions might be enhanced if the researchers concurrently conduct an interpretive study to examine the process of implementing the intervention or improvement.
    • Nested design - qualitative and quantitative methods can be integrated into a single research study.  For example, qualitative studies can be used to understand and operationalize key variables at the same time outcomes are evaluated.
    • Sequential design - the result of one method informs the results of another study. For example, using field methods to develop key variables before developing measurement instruments.
    • Combination design - case study design that combines multiple methods in order to understand the complexity of a setting. For example, a researcher may combine field methods sequentially with survey techniques, interviewing and record or chart review.

A good rule of thumb is that the multimethod design developed for a study should be such that it addresses the research questions posed.

Some authors have noted that study designs that link qualitative and quantitative methods for purposes of confirmation or convergence of methods can be problematic.  The differences in results that each method will produce may be difficult to reconcile. 

Note that the concurrent design described by Miller and Crabtree above does not seek convergence among qualitative and quantitative data sources, but complementarity.

When analyzing qualitative and quantitative data, consider approaches for translating qualitative data into a quantitative form (e.g. coding themes numerically) and translating quantitative data into a qualitative form (e.g. developing narrative summaries of quantitative data).  This will allow analysts to look across datasets and may foster more creative analyses.


Creswell, JW. (2003). Research Design: Qualitative and Quantitative and Mixed-Method Approaches. Thousand Oaks, CA: Sage Publications.

Greene, JC., Caracelli, VJ., Graham, WF. (1989). "Toward a conceptual framework for mixed-method evaluation designs." Educational Evaluation and Policy Analysis. 11, 255-274.

Greene, JC, & Caracell, VJ. (Eds). (1997). Advances in Mixed Methods Evaluation: The Challenges and Benefits of Integrating Diverse Paradigms. San Francisco: Jossey-Bass.

Miles, MB. & Huberman, AM. (1994). Qualitative Data Analysis: An Expanded Sourcebook (2nd Edition). Thousand Oaks, CA: Sage Publications.  Particularly pp. 40-43.

Miller, WL. & Crabtree, BF. (1994). "Clinical Research." In NK Denzin and YS Lincoln (Eds.) Handbook of Qualitative Research (pp. 340-352). Thousand oaks, CA: Sage Publications.

Morgan, DL. (1998). "Practical strategies for combining qualitative and quantitative methods: Applications to health research." Qualitative Health Research, 8(3), 362-376.

Rossman, GB. & Wilson, BL. (1985). "Numbers and words: Combining qualitative and quantitative methods in a single large scale evaluation." Evaluation Review, 9(5), 627-643.

Rossman, GB. & Wilson, BL. (1994). "Numbers and words revisited: Being shamelessly eclectic." Quality and Quantity, 28(3), 315-327.

Sandelowski, M. (2000). "Combining qualitative and quantitative sampling, data collection and analysis techniques in mixed-method studies." Res Nurs Health 23(3), 245-255.

Sandelowski, M. (1995). "Triangles and crystals: On the geometry of qualitative research." Res Nurs Health, 18(6), 569-574.

Stange, KC., Miller, WL., Crabtree, BF., O'Conner, PJ, & Zyzanski, SJ. (1994). "Multimethod research: Approaches to integrating qualitative and quantitative methods." Archives of General Internal Medicine, 9(5), 278-282.

Steckler, A., McLeroy, KR, Goodman, RM, Bird, ST, & McCormick, L. (1992). "Toward integrating qualitative and quantitative methods: An introduction." Health Education Quarterly, 19(1), 1-18.