Qualitative data analysis


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  • See Computer Assisted Qualitative Data Analysis CAQDAS See Edmonton Qualitative Web Ring See See Weitzman and Miles (1995) Computer Programs for Qualitative Analysis
  • Qualitative data analysis

    1. 1. Qualitative Data Analysis
    2. 2. Part 1 QDA Methods Outcomes – learners understand the origin and current practice of QDA methods in general, grounded theory in particular, and possible applications of the methods.
    3. 3. 1. Methods a. useful for inductive research b. useful in naturalistic inquiry c. qualitative methods growing consensus d. collection ↔ analysis ↔ collection
    4. 4. 2. Qualitative Data (QD) a. open b. exploratory c. useful when questions to ask not yet been defined d. allows insights
    5. 5. 3. Overview of QDA
    6. 6. 4. QDA cycle
    7. 7. 5. overview of process
    8. 8. 6. Work plan of research process
    9. 9. 7. Characteristics of QDA a. constructivist - many meanings b. context bound ie "book is in the pen" c. uses inflection ie "THIS was good." d. can be sorted in many ways e. QD by itself has meaning ie “apple”
    10. 10. 8. Sources of QD a. interviews b. focus Groups c. field observations d. survey comments e. historical records f. secondary data g. photos, paintings, songs ...
    11. 11. 9. Types of Qualitative Data a. structured text, (writings, stories, survey comments, news articles, books etc) b. unstructured text (transcription, interviews, focus groups, conversation) c. audio recordings, as above, music d. video recordings, as above (graphics, art, pictures, visuals)
    12. 12. 10. Methods Matched to Type of Data a. structured text b. unstructured text c. audio/ ie. interviews, anecdotes, “stories” d. video/graphics
    13. 13. 11. Methods Matched to Principle Task a. reduce amount of data Matrix analysis b. derive new ideas and insights Phenomenology c. test significance of ideas Post coding, Matrix analysis d. map theoretical relation of ideas Grounded Theory Mapping
    14. 14. 12. Principles of QDA (J. Morse) a. Data entry (gathering) b. Comprehending (immersion) c. Synthesizing (sifting) d. Theorizing (sorting) e. Re‑Contextualizing (emerging theory)
    15. 15. 13. Data entry (analogous demonstration) a. not easily mechanized b. important part of process c. often done by analyst d. concurrent with analysis e. transcribe thoroughly, ASAP f. write memos (reflect) g. coding (start with few)
    16. 16. 14. Comprehending (immersion) a. begin while entering data b. start QDA immediately c. “live with it” d. line by line examination e. create new questions for collection
    17. 17. 15. Synthesizing (sifting) “quotes” (decontextualize) a. use inductive categories b. find common threads c. compare transcripts d. aggregate stories
    18. 18. 16. Theorizing (sorting) “coding” a. ask questions of the data b. find alternative explanations c. allow sufficient time d. be open to insights
    19. 19. 17. Re‑Contextualizing (grounded theory) a. develop theoretical “elegance” b. apply to other settings c. examine fit to literature/research d. describe emerging theory
    20. 20. 18. Data Management Principles a. stay close to the data b. be sensitive to emergent theory c. allow recontextualizing d. it is a non‑linear process
    21. 21. 19. Grounded TheoryPrimary documents (comprehending) immerse in the primary documents begin as data are collected read/view/listen to the data
    22. 22. b. Quotations (synthesizing) select and mark salient quotations/passages compare each line to other data
    23. 23. c. Coding (theorizing) assign codes in margin group, sort, categorize codes into families collect new data based on emerging theory, memos, codes
    24. 24. d. Memos (aids in all processes) record insights on memos or post-it notes ie: ideas for emerging theories, thematic ideas, linked memos
    25. 25. e. Network (re- contextualizing) create a network view (mind map) add and arrange network nodes (quotes, memos and codes) collect more data as needed
    26. 26. f. Presenting (computer methods) display quote and code lists display node “mind-map” – export network .jpg into Word export quotation data into SPSS.sps, – run crosstab (matrix) export .html web page for multimedia use
    27. 27. 20. Q&A Questions and answers
    28. 28. Part 2. EXERCISES
    29. 29. Part 3. QDA SOFTWARE OVERVIEW Outcomes – learners will know how to choose among a few types of qualitative data analysis software, and their application to analyzing various qualitative data using QDA methods.
    30. 30. Some QDA Methods (and Software)1. Post-coding ie. using SPSS, Excel2. Matrix analysis ie. using Nud●Ist, SPSS3. Phenomenology - using mind maps ie. Inspiration, Atlas-ti4. Grounded Theory Mapping ie. Atlas-ti
    31. 31. Uses of computer software in Qualitative Studiesa. writing/editing the datab. storage of datac. coding data (keywords or tags)d. search and retrieval of datae. data linking of related textf. writing/editing memos about the datag. content analysish. display of selected reduced datai. conclusion drawingj. theory building - create explanationsk. graphic mappingl. preparing reports Miles and Huberman 1994
    32. 32. How to choose software - Key Questionsa. kind and amount of data?b. choosing for 1 project or next few yrs?c. theoretical approach to analysis?d. time to learn vs time to analyze?e. simplicity or detailed analysis?f. desired “closeness” to the datag. any desired quantification of results?h. individual or working as a team?i. peer software support available?j. Any cost constraints? (Weitzman and Miles 1995; Lewins and Silver 2005).
    33. 33. Audio Data Analysis Using Atlas-ti 5.0 - demo These slides at cesbc.ca Go to Links
    34. 34. QDA software Atlas-ti (Scientific Software Germany) NVivo (QSR Australia) Inspiration (USA) Concept Systems (USA) Excel, Access, SPSS (USA)
    35. 35. Methodological foundations Grounded Theory (i.e. Glaser and Strauss) Coding (i.e. Morse) Thematic Analysis (i.e. Giorgi)
    36. 36. Atlas-ti Visual Qualitative Data Analysis Management and Model Building
    37. 37. Steps in Atlas-ti1. Load primary documents2. Mark “quotes”3. Create codes, drag and drop on quotes4. Retrieve coded quotes, conduct queries5. Write memos6. Draw network models, draw conclusions
    38. 38. Features• Allows many types of primary documents: graphics, audio, video
    39. 39. All share the same code set• Quotations to the letter or milli-second• Queries retrieve and (dis)play all quotes• Networks (dis)play all nodes and quotes• Exports to SPSS data and syntax• Exports to html
    40. 40. Disadvantages• No matrix output display• Cannot edit Word docs or use Word tables• No drag and drop onto audio/video player