15 Methods of Data Analysis in Qualitative Research
Compiled by Donald Ratcliff

1. Typology - a classification system, taken from patterns, themes, or other kinds of
groups of data. (Patton pp. 393,398) John Lofland & Lyn Lofland
Ideally, categories should be mutually exclusive and exhaustive if possible, often they
aren't.
Basically a list of categories. example: Lofland and Lofland's 1st edition list: acts,
activities, meanings, participation, relationships, settings (in the third edition they have
ten units interfaced by three aspects--see page 114--and each cell in this matrix might be
related to one of seven topics--see chapter seven).

2. Taxonomy (See Domain Analysis - often used together, especially developing
taxonomy from a single domain.) James Spradley
A sophisticated typology with multiple levels of concepts. Higher levels are inclusive of
lower levels.
Superordinate and subordinate categories

3. Constant Comparison/Grounded Theory (widely used, developed in late 60's)
Anselm Strauss
• Look at document, such as field notes
• Look for indicators of categories in events and behavior - name them and code
them on document
• Compare codes to find consistencies and differences
• Consistencies between codes (similar meanings or pointing to a basic idea)
reveals categories. So need to categorize specific events
• We used to cut apart copies of field notes, now use computers. (Any good word
processor can do this. Lofland says qualitative research programs aren't all that
helpful and I tend to agree. Of the qualitative research programs I suspect that
NUD*IST probably the best--see Sage Publishers).
• Memo on the comparisons and emerging categories
• Eventually category saturates when no new codes related to it are formed
• Eventually certain categories become more central focus - axial categories and
perhaps even core category.

4. Analytic Induction (One of oldest methods, a very good one) F. Znaniecki, Howard
Becker, Jack Katz. I wrote a paper on the topic.
Look at event and develop a hypothetical statement of what happened. Then look at
another similar event and see if it fits the hypothesis. If it doesn't, revise hypothesis.
Begin looking for exceptions to hypothesis, when find it, revise hypothesis to fit all
examples encountered. Eventually will develop a hypotheses that accounts for all
observed cases.

5. Logical Analysis/Matrix Analysis An outline of generalized causation, logical
reasoning process, etc.
Use flow charts, diagrams, etc. to pictorially represent these, as well as written
descriptions.
Matthew Miles and Huberman gives hundreds of varieties in their huge book Qualitative
Data Analysis, 2nd ed.

6. Quasi-statistics (count the # of times something is mentioned in field notes as very
rough estimate of frequency) Howard Becker
Often enumeration is used to provide evidence for categories created or to determine if
observations are contaminated. (from LeCompte and Preissle).

7. Event Analysis/Microanalysis (a lot like frame analysis, Erving Goffman) Frederick
Erickson, Kurt Lewin, Edward Hall.
Emphasis is on finding precise beginnings and endings of events by finding specific
boundaries and things that mark boundaries or events. Specifically oriented toward film
and video. After find boundaries, find phases in event by repeated viewing.

8. Metaphorical Analysis (usually used in later stages of analysis) Michael Patton, Nick
Smith

Try on various metaphors and see how well they fit what is observed. Can also ask
participant for metaphors and listen for spontaneous metaphors. "Hallway as a highway."
Like highway in many ways: traffic, intersections, teachers as police, etc.
Best to check validity of metaphor with participants - "member check".

9. Domain Analysis (analysis of language of people in a cultural context) James
Spradley
Describe social situation and the cultural patterns within it. Semantic relationships.
Emphasize the meanings of the social situation to participants. Interrelate the social
situation and cultural meanings.
Different kinds of domains: Folk domains (their terms for domains), mixed domains,
analytic domains (researcher's terms for domains).
• select semantic relationships
• prepare domain analysis worksheet
• select sample of field notes (statements of people studied)
• look for broad and narrow terms to describe semantic relationships
• formulate questions about those relationships
• repeat process for different semantic relationship
• list all domains discovered

10. Hermeneutical Analysis (hermeneutics = making sense of a written text) Max Van
Manen
Not looking for objective meaning of text, but meaning of text for people in situation. Try
to bracket self out in analysis - tell their story, not yours. Use their words, less
interpretive than other approaches.
Different layers of interpretation of text. Knowledge is constructed – we construct
meaning of text (from background and current situation - Social construction because of
influence of others - symbolic interactionism)
Use context - time and place of writing - to understand. What was cultural situation?
Historical context. Meaning resides in author intent/purpose, context, and the
encounter between author and reader - find themes and relate to dialectical context.
(Some say authorial intent is impossible to ascertain.)

Videotape - probably needs to be secondary level of analysis. Get with another person
who is using another method and analyze their field notes.

11. Discourse analysis (linguistic analysis of ongoing flow of communication) James
Gee
Usually use tapes so they can be played and replayed. Several people discussing, not
individual person specifically. Find patterns of questions, who dominates time and how,
other patterns of interaction.

12. Semiotics (science of signs and symbols, such as body language) Peter Manning
Determine how the meanings of signs and symbols is constructed. Assume meaning is
not inherent in those, meaning comes from relationships with other things. Sometimes
presented with a postmodernist emphasis.

13. Content Analysis (not very good with video and only qualitative in development of
categories - primarily quantitative) (Might be considered a specific form of typological
analysis) R. P. Weber
Look at documents, text, or speech to see what themes emerge. What do people talk
about the most? See how themes relate to each other. Find latent emphases, political view
of newspaper writer, which is implicit or look at surface level - overt emphasis.
Theory driven - theory determines what you look for. Rules are specified for data
analysis.
Standard rules of content analysis include:
• How big a chunk of data is analyzed at a time (a line, a sentence, a phrase, a
paragraph?) Must state and stay with it.
• What are units of meaning?, the categories used. Categories must be:
1. Inclusive (all examples fit a category)
2. Mutually exclusive
• Defined precisely: what are properties
• All data fits some category (exhaustive)

Also note context. Start by reading all way through, then specify rules. Could have
emergent theory, but usually theory-driven. After determine categories, do the counting -
how often do categories occur. Most of literature emphasizes the quantitative aspects.
Originated with analyzing newspaper articles for bias - counting things in print. Very
print oriented - can it be adapted for visual and verbal?

14. Phenomenology/Heuristic Analysis (phenomenological emphasis - how individuals
experience the world) Clark Moustakas
Emphasizes idiosyncratic meaning to individuals, not shared constructions as much.
Again, try to bracket self out and enter into the other person's perspective and experience.
Emphasizes the effects of research experience on the researcher-personal experience of
the research. How does this affect me as researcher. Much like hermeneutical analysis,
but even more focused on the researcher's experience. Some use the term
"phenomenology" to describe the researcher's experience and the idea that this is all
research is or can ever be (see Lofland and Lofland, p. 14).

15. Narrative Analysis (study the individual's speech) Catherine Reisman
Overlaps with other approaches. (Is it distinctive?) Discourse analysis looks at
interaction, narrative is more individual)
The story is what a person shares about self. What you choose to tell frames how you will
be perceived. Always compare ideas about self. Tend to avoid revealing negatives about
self. Might study autobiographies and compare them.
• context-situation
• core plot in the story told about self
• basic actions
Narrative analysis could involve study of literature or diaries or folklore.

References

Taxonomic Analysis: James P. Spradley (1980). Participant observation. Fort Worth: Harcourt
Brace.
Typological Systems: John Lofland & Lyn H. Lofland (1995). Analyzing social settings, 3rd ed.
Belmont, Cal.: Wadsworth.

Constant Comparison: Anselm L. Strauss (1987). Qualitative analysis for social scientists. New
York: Cambridge University Press.
Case Study Analysis: Sharon Merriam (1988). Case study research in education. Jossey-Bass.
Ethnostatistics: Robert P. Gephart (1988). Ethnostatistics: Qualitative foundations for
quantitative research. Newbury Park, Cal.: Sage Publications.
Logical Analysis/Matrix Analysis: Miles, M. B., & Huberman, A. M. (1994). Qualitative data
analysis, 2nd ed. Newbury Park, Cal.: Sage. [Note: I think this may well be the best book
available on qualitative data analysis.]
Phenomenological/Heuristic Research: Moustakas, C. (1990). Heuristic Research. Newbury Park,
Cal.: Sage; and Moustakas, C. (1994). Phenomenological research methods. Newbury Park, Cal.:
Sage.
Event Analysis/Microanalysis: Frederick Erickson (1992). Ethnographic microanalysis of
interaction. In M. LeCompte, et. al. (Eds), The handbook of qualitative research in education
(chapter 5). San Diego: Academic Press.
Analytic Induction: Jack Katz (1983). A theory of qualitative methodology. In R. M. Emerson
(Ed.), Contemporary field research. Prospect Heights, Ill.: Waveland.
Hermeneutical Analysis: Max Van Manen (1990). Researching lived experience. New York:
State University of New York Press.
Semiotics: Peter K. Manning (1987). Semiotics and fieldwork. Newbury Park, Cal.: Sage.
Discourse Analysis: James P. Gee (1992). Discourse analysis. In M. LeCompte, et. al. (Eds), The
handbook of qualitative research in education (chapter 6). San Diego: Academic Press.
Narrative Analysis: Catherine K. Reisman (1993). Narrative analysis. Newbury Park, Cal.: Sage.
Content Analysis: R. P. Weber (1990). Basic content analysis. Newbury Park, Cal.: Sage.
Domain Analysis: James P. Spradley (1980). Participant observation. Fort Worth: Harcourt
Brace. Also see J. P. Spradley, Ethnographic interview (1979, same publisher).
Metaphorical Analysis: Nick Smith (1981). Metaphors for evaluation. Newbury Park, Cal.: Sage.