Lecture 7: Qualitative Data Analysis Flashcards

1
Q

Principles qualitative data analysis

A
  • noticing concepts
  • collecting examples of these concepts
  • analyzing these concepts in order to find commonalities
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2
Q

Three principles of qualitative analysis

A

Describe
Connect
Classify

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3
Q

Different types of analysis

A
  • content analysis
  • thematic analysis
  • grounded theory
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4
Q

Code

A

word or short phrase that represent the essence or key attribute of narrative/verbal information

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5
Q

Content analysis

A

categories based on conceptual framework (deductive)

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6
Q

Grounded theory

A

from transcript emerges concepts and categories (inductive)

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7
Q

Vertical analysis

A
  • focused on understanding the essence of individual interviews
  • establishing links between codes
  • narrative
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8
Q

Horizontal analysis

A
  • focused on aggregation and comparison of content of data across different interviews
  • good overview of topics that have been covered
  • content
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9
Q

Three levels of coding

A
  • open
  • axial
  • selecting
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10
Q

Open coding

A
  • concepts are identified
  • properties and dimensions discovered in data
  • very vertical
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11
Q

Axial coding

A
  • relating categories to subcategories
  • linking categories at level of properties and dimensions
  • very horizontal
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12
Q

Sensitive/selecting coding

A
  • integrating and refining theory
  • defining categories
  • determining key concepts and formulate the essence of key concepts vs line of argumentation
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13
Q

External validity

A

if the findings are generalizable to other social settings similarity with theory
how outcomes of the study is related with the outside world.

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14
Q

Internal validity

A

there is a strong link between data and theoretical ideas developed

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15
Q

Increase internal validity

A
  • member checking
  • expert checking
  • analysing negative cases
  • performing a literature review beforehand (as input for design)
  • triangulation
  • training of researcher
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16
Q

Increase external validity

A

compare with literature

17
Q

Two types of data saturation

A
  • Theoretical saturation = collected data adds nothing new to developing theory
  • Coding saturation = no more emerging codes