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RS blok 4 > L5 - qualitative: analyzing > Flashcards

L5 - qualitative: analyzing Flashcards

1
Q

examples of analysis types > 4

A
  1. Grounded theory analysis
  2. Narrative analysis
  3. Content analysis
  4. Thematic analysis
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2
Q

example of thematic analysis

A

coding

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3
Q

stages of qualitative data analysis

A
  1. Data reduction > organize + reduce data (based on research question)
  2. Data display > make tables, charts, networks, codes (= continual)
  3. Data categorization > group different categories of information
  4. Potential addition: Data contextualization > assembly collected information + external contingencies > identify links + connections
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4
Q

how increase trustworthiness > 5

A
  1. Member validation > let subject criticize findings
  2. Search for negative cases + alternative explanations
  3. Triangulate > combine different sources
  4. Audit trail > key decisions should be explained to be judged
  5. Reflexivity > researcher should critically reflect own role in data collection process and explain potential implications to reader
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5
Q

coding

what, why, how, criteria

A

What: Tags / labels
Why: retrieve + organize data
How: look for patterns + regularities, identify key words + supporting/refuting statements
Criteria: valid + mutually exclusive + exhaustive

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6
Q

stages coding

A 
stage 1. Read + categorize data
	Ask yourself the following questions:
		- What type of behaviors
		- What is the structure
		- What is the frequency
		- What are the causes
		- What are the processes
		- What are the consequences
		- What are strategies

stage 2. Open + axial + selective coding
Level 1: open coding > Identify themes
Themes are generated NOT emerged
Level 2: axial coding > refine + align + categorize themes
Six C’s model: constant comparison of codes and refinement (causes, context, contingencies, consequences, covariance, conditions)
Level 3: selective coding > select + integrate codes
Which codes can be combined within 1 category?
Is there an order? Sequential coding
Can I identify any causal relationships?

• Organization of Coded Data Step 1: Cluster data units into themes (/codes) > group units together into first order themes  Step 2: Repeat by grouping first order themes into second order themes 
	• Qualitative Data Software = QDA
	Why use:
	- Make notes
	- Editing 
	- Memos
	- Coding 
	- Storage
	- Search + retrieval 
	- Data linking
	- Content analysis
	- Data display 
	- Condensed format
	- Conclusion drawing + verification
	- Theory-building
	- Graphic mapping
	- Preparing reports
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7
Q

Confirmation bias

A

seek data that supports your own ideas

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8
Q

names of QDA

A

Nvivo > mixed
Atlas/ti > only qualitative
MaxQDA > mixed

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9
Q

Gioia Methodology

A

first order codes > second order codes > aggregate dimensions

Data structure > theory: conceptual framework > writing > transferability

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10
Q

How assess quality in research

A

Validity + reliability

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11
Q

Critique in qualitative field + goal

A

Critique:

  • Subjective results + anecdotes
  • Lack of precision in measurement
  • Lack of qualitative rigor

partly due to positivist approach

Goal:

  • Establishing trustworthiness research
  • Showing warrant inferences
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12
Q

Lincoln and Guba 1985 regarding trustoworthiness qualitative research

A
  1. Credibility
  2. Transferability
  3. Confirmability
  4. Dependability
    Based on constructive paradigm = subjective = multiple realities
  5. Later added: authenticity
    Assess quality in qualitative research by different philosophical paradigms
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13
Q

How approach trustworthiness Guba (1981):

aspect - scientific - naturalisic - results

A

Truth value - Internal validity - Credibility - About real thing

Applicability - External validity / generalizability - Transferability - Apply to other context

Consistency - Reliability - Dependability - Skewed by method - Neutrality

Objectivity - Confirmability - Depend on researcher

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14
Q

problems qualitative research > 4

A

Problem 1: many interlocking factors > credibility
Does it research the real thing?
- Triangulation > data sources, investigators, perspectives
- Lengthy + intense engagement > biases, perceptions, influence researcher
- Persistent inquiry > essential vs irrelevant qualities
- Member check > check interpretations / findings with focus audience
- Peer debriefing > feedback from researchers
- Structural coherence > test data through constant comparison + explain deviant cases

Problem 2: Behavior is context bound + situational uniqueness > transferability 
Does it really apply to other contexts? 
	- thick description context 
	- collect rich data 
	- purposeful sampling

Problem 3: unstable instruments + conflicting data (affects variation) > dependability
Would researcher with different understandings/social realities generate same results?
- Overlapping methods
- Stepwise replication
- Audit trail
- Dependability audit: peer check data + analysis process

Problem 4: researcher bias + preconceptions influence findings > confirmability

- Confirmability audit > peer check data vs interpretations and interpretations vs data 
- Triangulation
- Practice reflexivity > reflect how ontological (concepts/relationships), epistemological (knowledge),  theoretical (theoretic knowledge) preconceptions influence data
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15
Q

qualitative research process

A

research problem
RQ
>< literature review

data collection
data analysis
>< methods and techniques

conclusion

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16
Q

qualitative thesis framework

A

A Introduction

  1. Abstract
  2. Purpose
  3. RQ’s (1 can be sufficient)
  4. Definition key concepts

B Frame of reference

  1. Research problem
  2. Literature review
  3. RQ’s

C Research methodology

  1. Research strategy
  2. Research method
  3. Data collection + sampling
  4. Data analysis
  5. Quality + trustworthiness

D Findings
Note: NO theory or interpretations

E Analysis
1. Interpretation
2. Contributions (models, propositions, typologies, new concepts)
Note: Interpretations + knowledge contributions

F Conclusions

  1. Theoretical implications (=answer RQ)
  2. Ethical implications
  3. Managerial implications
  4. Limitations
  5. Future research suggestions
17
Q

quantitative thesis framework

A

Introduction

  1. Abstract
  2. Purpose
  3. RQ’s (1 can be sufficient)
  4. Definition key concepts

Note: is long abstract, adapt afterwards

Theory

1. Research problems 
2. Literature review

Hypothesis

1. Theoretical model
2. Formulation hypothesis

Method

1. Research strategy
2. Research method
3. Data
4. Variables and measures
5. Validity + reliability

Results

1. Descriptive statistics
2. Correlation table
3. Regression analysis
4. Robustness tests

Note: mention if hypotheses are supported. DON’T LINK WITH THEORY.

Discussion and conclusions

  1. Theoretical implications
  2. Ethical implications
  3. Managerial implications
  4. Limitations
  5. Future research suggestions

RS blok 4 (10 decks)

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