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Qualitative Data Analysis Methods

In the following, we will discuss basic approaches to analyzing data in all six of the acceptable qualitative designs.

Objectives

After reviewing the information in this document, you will be able to:

• Recognize the terms for data analysis methods used in the various acceptable designs.
• Recognize the data preparation tasks that precede actual analysis in all the designs.
• Understand the basic analytic methods used by the respective qualitative designs.
• Identify and apply the methods required by your selected design.

Terms Used in Data Analysis by the Six Designs

Each qualitative research approach or design has its own terms for methods of data analysis:

• Ethnography—uses modified thematic analysis and life histories.
• Case study—uses description, categorical aggregation, or direct interpretation.
• Grounded theory—uses open, axial, and selective coding (although recent writers are proposing variations on those basic analysis methods).
• Phenomenology—describes textures and structures of the essential meaning of the lived experience of the phenomenon
• Heuristics—patterns, themes, and creative synthesis along with individual portraits.
• Generic qualitative inquiry—thematic analysis, which is really a foundation for all the other analytic methods. Thematic analysis is the starting point for the other five, and the endpoint for generic qualitative inquiry. Because it is the basic or foundational method, we'll take it first.

Preliminary Tasks in Analysis in all Methods

In all the approaches—case study, grounded theory, generic inquiry, and phenomenology—there are preliminary tasks that must be performed prior to the analysis itself. For each, you will need to:

• Arrange for secure storage of original materials. Storage should be secure and guaranteed to protect the privacy and confidentiality of the participants' information and identities.
• Transcribe interviews or otherwise transform raw data into usable formats.
• Make master copies and working copies of all materials. Master copies should be kept securely with the original data. Working copies will be marked up, torn apart, and used heavily: make plenty.
• Arrange secure passwords or other protection for all electronic data and copies.
• When ready to begin, read all the transcripts repeatedly—at least three times—for a sense of the whole. Don't force it—allow the participants' words to speak to you.

These tasks are done in all forms of qualitative analysis. Now let's look specifically at generic qualitative inquiry.

Data Analysis in Generic Qualitative Inquiry: Thematic Analysis

The primary tool for conducting the analysis of data when using the generic qualitative inquiry approach is thematic analysis, a flexible analytic method for deriving the central themes from verbal data. A thematic analysis can also be used to conduct analysis of the qualitative data in some types of case study.

Thematic analysis essentially creates theme-statements for ideas or categories of ideas (codes) that the researcher extracts from the words of the participants.

There are two main types of thematic analysis:

• Inductive thematic analysis, in which the data are interpreted inductively, that is, without bringing in any preselected theoretical categories.
• Theoretical thematic analysis, in which the participants' words are interpreted according to categories or constructs from the existing literature.

Analytic Steps in Thematic Analysis: Reading

Remember that the last preliminary task listed above was to read the transcripts for a sense of the whole. In this discussion, we'll assume you're working with transcribed data, usually from interviews. You can apply each step, with changes, to any kind of qualitative data. Now, before you start analyzing, take the first transcript and read it once more, as often as necessary, for a sense of what this participant told you about the topic of your study. If you're using other sources of data, spend time with them holistically.

Thematic Analysis: Steps in the Process

When you have a feel for the data,

1. Underline any passages (phases, sentences, or paragraphs) that appear meaningful to you. Don't make any interpretations yet! Review the underlined data.
2. Decide if the underlined data are relevant to the research question and cross out or delete all data unrelated to the research question. Some information in the transcript may be interesting but unrelated to the research question.
3. Create a name or "code" for each remaining underlined passage (expressions or meaning units) that focus on one single idea. The code should be:
• Briefer than the passage, should
• Sum up its meaning, and should be
• Supported by the meaning unit (the participant's words).
4. Find codes that recur; cluster these together. Now begin the interpretation, but only with the understanding that the codes or patterns may shift and change during the process of analysis.
5. After you have developed the clusters or patterns of codes, name each pattern. The pattern name is a theme. Use language supported by the original data in the language of your discipline and field.
6. Write a brief description of each theme. Use brief direct quotations from the transcript to show the reader how the patterns emerged from the data.
7. Compose a paragraph integrating all the themes you developed from the individual's data.
8. Repeat this process for each participant, the "within-participant" analysis.
9. Finally, integrate all themes from all participants in "across-participants" analysis, showing what general themes are found across all the data.

Some variation of thematic analysis will appear in most of the other forms of qualitative data analysis, but the other methods tend to be more complex. Let's look at them one at a time. If you are already clear as to which approach or design your study will use, you can skip to the appropriate section below.

Ethnographic Data Analysis

Ethnographic data analysis relies on a modified thematic analysis. It is called modified because it combines standard thematic analysis as previously described for interview data with modified thematic methods applied to artifacts, observational notes, and other non-interview data.

Depending on the kinds of data to be interpreted (for instance pictures and historical documents) Ethnographers devise unique ways to find patterns or themes in the data.
Finally, the themes must be integrated across all sources and kinds of data to arrive at a composite thematic picture of the culture.

(Adapted from Bogdan and Taylor, 1975; Taylor and Bogdan, 1998; Aronson, 1994.)

Data Analysis in Grounded Theory

Going beyond the descriptive and interpretive goals of many other qualitative models, grounded theory's goal is building a theory. It seeks explanation, not simply description.

It uses a constant comparison method of data analysis that begins as soon as the researcher starts collecting data. Each data collection event (for example, an interview) is analyzed immediately, and later data collection events can be modified to seek more information on emerging themes.

In other words, analysis goes on during each step of the data collection, not merely after data collection.

The heart of the grounded theory analysis is coding, which is analogous to but more rigorous than coding in thematic analysis.

Coding in Grounded Theory Method

There are three different types of coding used in a sequential manner.

1. The first type of coding is open coding, which is like basic coding in thematic analysis. During open coding, the researcher performs:
• A line-by-line analysis (or sentence or paragraph analysis) of the data.
• Labels and categorizes the dimensions or aspects of the phenomenon being studied.
• The researcher also uses memos to describe the categories that are found.
2. The second type of coding is axial coding, which involves finding links between categories and subcategories found in the open coding.
• The open codes are examined for their relationships: cause and effect, co-occurrence, and so on.
• The goal here is to picture how the various dimensions or categories of data interact with one another in time and space.
3. The third type of coding is selective coding, which identifies a core category and relates the categories subsidiary to this core.
• Selective coding selects the main phenomenon, (core category) around which subsidiary phenomena, (all other categories) are grouped, arranging the groupings, studying the results, and rearranging where the data require it.

The Final Stages of Grounded Theory Analysis, after Coding

From selective coding, the grounded theory researcher develops:

• A model of the process, which is the description of which actions and interactions occur in a sequence or series.
• A transactional system, which is the description of how the interactions of different events explain the phenomenon being investigated.
• Finally, A conditional matrix is diagrammed to help consider the conditions and consequences related to the phenomenon under study.

These three essentially tell the story of the outcome of the research, in other words, the description of the process by which the phenomenon seems to happen, the transactional system supporting it, and the conditional matrix that pictures the explanation of the phenomenon are the findings of a grounded theory study.

(Adapted from Corbin and Strauss, 2008; Strauss and Corbin, 1990, 1998.)

Data Analysis in Qualitative Case Study: Background

There are a few points to consider in analyzing case study data:

• Analysis can be:
• Holistic—the entire case.
• Embedded—a specific aspect of the case.
• Multiple sources and kinds of data must be collected and analyzed.
• Data must be collected, analyzed, and described about both:
• The contexts of the case (its social, political, economic contexts, its affiliations with other organizations or cases, and so on).
• The setting of the case (geography, location, physical grounds, or set-up, business organization, etc.).

Qualitative Case Study Data Analysis Methods

Data analysis is detailed in description and consists of an analysis of themes. Especially for interview or documentary analysis, thematic analysis can be used (see the section on generic qualitative inquiry). A typical format for data analysis in a case study consists of the following phases:

• Description: This entails developing a detailed description of each instance of the case and its setting. The words "instance" and "case" can be confusing. Let's say we're conducting a case study of gay and lesbian members of large urban evangelical Christian congregations in the Southeast. The case would be all such people and their congregations. Instances of the case would be any individual person or congregation. In this phase, all the congregations (the settings) and their larger contexts would be described in detail, along with the individuals who are interviewed or observed.
• Categorical Aggregation: This involves seeking a collection of themes from the data, hoping that relevant meaning about lessons to be learned about the case will emerge. Using our example, a kind of thematic analysis from all the data would be performed, looking for common themes.
• Direct Interpretation: By looking at the single instance or member of the case and drawing meaning from it without looking for multiple instances, direct interpretation pulls the data apart and puts it together in more meaningful ways. Here, the interviews with all the gay and lesbian congregation members would be subjected to thematic analysis or some other form of analysis for themes.
• Within-Case Analysis: This would identify the themes that emerge from the data collected from each instance of the case, including connections between or among the themes. These themes would be further developed using verbatim passages and direct quotation to elucidate each theme. This would serve as the summary of the thematic analysis for each individual participant.
• Cross-Case Analysis: This phase develops a thematic analysis across cases as well as assertions and interpretations of the meaning of the themes emerging from all participants in the study.
• Interpretive Phase: In the final phase, this is the creation of naturalistic generalizations from the data as a whole and reporting on the lesson learned from the case study.

(Adapted from Creswell, 1998; Stake, 1995.)

Data Analysis in Phenomenological Research

There are a few existing models of phenomenological research, and they each propose slightly different methods of data analysis. They all arrive at the same goal, however. The goal of phenomenological analysis is to describe the essence or core structures and textures of some conscious psychological experience. One such model, empirical, was developed at Duquesne University. This method of analysis consists of five essential steps and represents the other variations well. Whichever model is chosen, those wishing to conduct phenomenological research must choose a model and abide by its procedures. Empirical phenomenology is presented as an example.

1. Sense of the whole. One reads the entire description in order to get a general sense of the whole statement. This often takes a few readings, which should be approached contemplatively.
2. Discrimination of meaning units. Once the sense of the whole has been grasped, the researcher returns to the beginning and reads through the text once more, delineating each transition in meaning.
• The researcher adopts a psychological perspective to do this. This means that the researcher looks for shifts in psychological meaning.
• The researcher focuses on the phenomenon being investigated. This means that the researcher keeps in mind the study's topic and looks for meaningful passages related to it.
• The researcher next eliminates redundancies and unrelated meaning units.
3. Transformation of subjects' everyday expressions (meaning units) into psychological language. Once meaning units have been delineated,
• The researcher reflects on each of the meaning units, which are still expressed in the concrete language of the participants, and describes the essence of the statement for the participant.
• The researcher makes these descriptions in the language of psychological science.
4. Synthesis of transformed meaning units into a consistent statement of the structure of the experience.
• Using imaginative variation on these transformed meaning units, the researcher discovers what remains unchanged when variations are imaginatively applied, and
• From this develops a consistent statement regarding the structure of the participant's experience.
• The researcher completes this process for each transcript in the study.
5. Final synthesis. Finally, the researcher synthesizes all of the statements regarding each participant's experience into one consistent statement that describes and captures [of] the essence of the experience being studied.

(Adapted from Giorgi, 1985, 1997; Giorgi and Giorgi, 2003.)

Data Analysis in Heuristics

Six steps typically characterize the heuristic process of data analysis, consisting of:

• Initial engagement.
• Immersion.
• Incubation.
• Illumination.
• Explication.
• Synthesis.

To start, place all the material drawn from one participant before you (recordings, transcriptions, journals, notes, poems, artwork, and so on). This material may either be data gathered by self-search or by interviews with co-researchers.

1. Immerse yourself fully in the material until you are aware of and understand everything that is before you.
2. Incubate the material. Put the material aside for a while. Let it settle in you. Live with it but without particular attention or focus. Return to the immersion process. Make notes where they would enable you to remember or classify the material. Continue this rhythm of working with the data and resting until an illumination or essential configuration emerges. From your core or global sense, list the essential components or patterns and themes that characterize the fundamental nature and meaning of the experience. Reflectively study the patterns and themes, dwell inside them, and develop a full depiction of the experience. The depiction must include the essential components of the experience.
3. Illustrate the depiction of the experience with verbatim samples, poems, stories, or other materials to highlight and accentuate the person's lived experience.
4. Return to the raw material of your co-researcher (participant). Does your depiction of the experience fit the data from which you have developed it? Does it contain all that is essential?
5. Develop a full reflective depiction of the experience, one that characterizes the participant's experience reflecting core meanings for the individuals as a whole. Include in the depiction, verbatim samples, poems, stories, and the like to highlight and accentuate the lived nature of the experience. This depiction will serve as the creative synthesis, which will combine the themes and patterns into a representation of the whole in an aesthetically pleasing way. This synthesis will communicate the essence of the lived experience under inquiry. The synthesis is more than a summary: it is like a chemical reaction, a creation anew.
6. Return to the data and develop a portrait of the person in such a way that the phenomenon and the person emerge as real.

(Adapted from Douglass and Moustakas, l985; Moustakas, 1990.)

References

Bogdan, R., & Taylor, S. J. (1975). Introduction to qualitative research methods: A phenomenological approach (3rd ed.). New York, NY: Wiley.

Corbin, J., & Strauss, A. (2008). Basics of qualitative research: Techniques and procedures for developing grounded theory (3rd ed.). Los Angeles, CA: Sage.

Creswell, J. W. (1998).Qualitative inquiry and research design: Choosing among five traditions. Thousand Oaks, CA: Sage.

Douglass, B. G., & Moustakas, C. (1985). Heuristic inquiry: The internal search to know. Journal of Humanistic Psychology, 25(3), 39–55.

Giorgi, A. (Ed.). (1985). Phenomenology and psychological research. Pittsburgh, PA: Duquesne University Press.

Giorgi, A. (1997). The theory, practice and evaluation of phenomenological methods as a qualitative research procedure. Journal of Phenomenological Psychology, 28, 235–260.

Giorgi, A. P., & Giorgi, B. M. (2003). The descriptive phenomenological psychological method. In P. M. Camic, J. E. Rhodes, & L. Yardley (Eds.), Qualitative research in psychology: Expanding perspectives in methodology and design (pp. 243–273). Washington, DC: American Psychological Association.

Moustakas, C. (1990). Heuristic research: Design, methodology, and applications. Newbury Park, CA: Sage.

Stake, R. E. (1995). The art of case study research. Thousand Oaks, CA: Sage.

Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park, CA: Sage.

Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Techniques and theory for developing grounded theory (2nd ed.). Thousand Oaks, CA: Sage.

Taylor, S. J., & Bogdan, R. (1998). Introduction to qualitative research methods: A guidebook and resource (3rd ed.). New York: Wiley.

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