L8 Qualitative data analysis Flashcards
When doing qualitative analysis, what are the assumptions?
- Reality is socially constructed
- Emic (insider’s point of view)
- Variables are complex, interwoven, and difficult to measure
- Researcher is own instrument
- No standardized procedures
- Personal involvement and partiality
- Empathic understanding
What are the characteristics of a qualitative researcher?
- Reflexive awareness
- Openness
- Sensitivity
During your research process, when do you think of analysis?
- During design phase: devise frameworks, interview guides
- During data collection: questioning, probing, co-construction of meaning
- Desk analysis: coding responses, (re)construct relevant concepts and themes, organize around core generalizations or ideas
What are the principles of qualitative analysis?
Describe, classify, connect
- Noticing concepts
- Collecting examples of these concepts
- Analyzing these concepts in order to find commonalities
What are the different types / degrees of analysis?
- Content analysis: who says what, to whom, and with what effect
- Thematic analysis: identifying, analyzing, and reporting patterns / themes within data
- Grounded theory: construction of theory through open analysis of data
–> no clear boundaries in types of analysis
What are codes?
= word or phrase that represets the essence or key attribute of narrative / verbal communication
- Used to categorize data
- Coding is the process of organizing the data into chunks that are alike
- Codes are developed into a coding guide
What is a coding guide?
- Compilation of emerging codes
- Brief definitions or properties for each code
- Provides guidance for when and how to use the codes
- Will evolve throughout the analysis
- You continuously have discussions with your research team
What is the added value of quotations?
- Bring reader to reality of the situation
- Support your analysis and findings
- Illustrative
- Range of issues
- Opposing views (between stakeholders)
- Think of anonymity
What are the steps for qualitative analysis?
- Data curation–> transcribe
- Collect - code - collect - code
- Read and re-read, focussed reading and open coding
- Close examination, label text with keywords. Reviewing and axial coding.
- Modify codes, remove duplications, hierarchical order, integrate theory, generate theory.
- Look for connections that emerge from the data
What is open coding and how do you do it?
= Analytical process through which concepts are identified; their properties and dimensions are discovered in data
- Ask the data specific set of Qs
- Analyze the data minutely
- Comparing text fragments on similarities / differences
- What is the underlying concept
- Labeling fragments with keywords: concepts and categories include as many as possible
- More horizontal analysis needed
- Deductive research is guided by theory–> testing hypothesis
- Inductive research is open to all concepts
What are the pitfalls of inductive and deductive research in open coding?
Deductive research: too much fitting in existing boxes (closed mind)
Inductive research: too free in accepting all concepts (messy code book)
What is axial coding and how do you do it?
= Process of relating categories to their subcategories; linking categories at the level of the properties and dimensions
- Examine a phenomenon in terms of properties and dimensions
- What is the underlying pattern?
- Link categories on that level
- More vertical analysis needed
- Deductive research is looking for relations as presented in theory
- Inductive research is often difficult to find evidence for relations
What are the pitfalls of inductive and deductive research in axial coding?
Deductive research: too much looking for evidence for relation (closed mind)
Inductive research: accepting too vague relations as the truth
What is selective coding?
= Process of integrating and refining theory; defining core categories; determining key concepts and formulate the essence of key concepts vs line of argumentation
What is horizontal analysis?
Focussed on aggregation and comparison of content of data across different interviews (or other data). Pay attention to diversity (both majority and minority of views count).
