Analytic Techniques and Data Management

Analytic Techniques and Data Management

1. DATA ANALYSIS STRATEGIES

   • Ethnographic analysis
     • Focus on the culture and social regularities of everyday life. Thick description. To reach across multiple data sources. Categories and subcategories
       • 1. The economy, 2. demographics, 3. basic situations of human life, 4. the environment
   • Narrative analysis
     • First person account of the experience form the narrative text. Autoboigraphy, life history, interview, journal, letters. Text is analysed using the techniques of a particular discipline
   • Phenomenological analysis
     • Ferreting out the basic the essence or the basic structure of a phenomenon using specific techniques: epoche, bracketing, imaginative variation, first and second order knowledge
   • The constant comparative method
     • Ground theory consists of categories, properties, and hypotheses constantly compared, The researcher begins with a particular incident from an interview, field notes, or document and compares it with another incident
   • Content analysis and analytic induction
     • Simultaneous coding of raw data and the construction of categories that capture relevant characteristics of the docuemnt's content

2. ANALYSIS DURING DATA COLLECTION

   • The right way to analyse data in a qualitative study is to do it simultaneosuly with data collection. You can do rudimentary analysis while you are in the process of collecting data
   • 1. Force yourself to make decisions that narrow the study
   • 2. Force yourself to make decisions concerning the type of study you want to conduct
   • 3. Develop analytic questions
   • 4. Plan data collection sessions according to what you find in previous observations
   • 5, Write many observer's comments
   • 6. Write memos to yourself about what you are learning
   • 7. Try out ideas and themes on subjects
   • 8. Begin exploring literature while you are in the field
   • 9. Play with metaphors, analogies, and concepts
   • 10. Use visual devices

3. MANAGING YOUR DATA

   • Data management and theory building
     • Three phases: data preparation, involves typing notes, transcribing interviews, entering the data from which the researcher will be working. Data identification and manipulation which process is the beggining of theory building. Deciding on categories (codes)invovles decisions about concepts
       • Office software
         • The strenghts of an standard word processor are often unmatched in more specialized software,
         • Footnoting, annotating, indexing, hypertext linking and embedding graphic and media files
         • The weaknesses are the inability to perform Boolean searches to isolate specific instances of multiple conditions
       • Qualitative software
         • QUALPRO, NUDIST and so on
         • Asses your own theoretical orientation, the type of data and projects with which you expect to work, and your resources as well as computer skills
         • Entry, organization, and manipulation of data
         • They are more systematic, more thorough, less likely to miss things, more flexible and faster
       • Issues in the use of qualitative software
         • That the tool will change the nature of the research ,
         • That they will distance the researcher from the data or introduce errors
         • Writing and reading field notes is an intimate process that is often self-revelatory
       • New developments
         • Multitasking,
         • Improved coding and chuncking abilities
         • Improved ability to handle both qualitative and quatitave research
         • Multimedia annotation tools
         • Improved coordination with other software programs
         • Better orientation of the data
         • More powerful search and retrieval functions
         • Easy audit trail creation
         • Accomodation of related factual information
         • Improved support for collaboration among members

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