Methods of Data Analysis in Qualitative Research

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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...
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