M4 - Quantitaive Research Flashcards
Disadvantages of Quantitative Research
- little information about the why and how / the mechanisms
- -> many possible interpretations of the answer ‘i dont know’
- analyzer has leeway in interpreting
- -> subjectivity?
+ can provide structured and adaptable answers
+ dors not have to take place in a laboratory
Advantages of Quantitative Research
- little information about the why and how / the mechanisms
- -> many possible interpretations of the answer ‘i dont know’
- analyzer has leeway in interpreting
- -> subjectivity?
+ can provide open, structured and adaptable questions
+ dors not have to take place in a laboratory
Disadvantages Qualitative R
- sample size Small number of research objects - choice of he sample (mostly no real random sample) - measures No metric (quantitative) variables - analysis No statistical analysis
—> high degree of subjectivity
Quant & Qualit ?
Qualitative research - generate hypotheses / help understand relationships/ mechanisms
Quantitative r - test the hypotheses / avoids being biased throigh qual. Data
They complement each other
Methods of qualitative r for data collection and analysis
Method:
- case study research (one or few firms)
- discours analysis (linguistic details being asked)
Data collection:
- quali. Interview (semi structured interview, open questions)
- ethnography
Data analysis:
- qualit content analysis
- quant content analysis
Qualitative content analysis
Quantitative content analysis
Qualitative:
A systematic and replicable technique for compressing many words of text into fewer content CATEGORIES bas on exolicit rules of CODING.
Quantitaive:
A systematic and replicable description of content through formal categorization of relevant features (e.g word frequencies)
Qualitative content analysis
- Is an analysis method without a priori formulated ….. …..
- …. can be created during the analysis
- …. and ….. ….. can be intertwined
Qualitative content analysis
- Is an analysis method without a priori formulated ANALYSIS CRITERIA
- CATEGORIES can be created during the analysis
- ANALYSIS and DATA COLLECTION can be intertwined
Aspects of Categories
- compeleteness
Ensures that the research can be fully adressed.
- exclusivity
Ensures that categories are non overlapping.
Completeness of categories
…ensures thattje research can be fully adressed.
Wrong categorization:
- too much/ too little weight on certain categories
- no clear understanding of mechanisms and relationships between categories
How to ensure completeness:
Careful assessment of existing concepts, adaptivity of new categories; add new category
Exclusivity of categories
What is it?
If not exclusive: categorization ambiguous
How to ensure exclusivity?
… exclusivity of categories ensures that categories are non-overlapping.
If not exclusive: categorization ambiguous
- no clear understanding of mechanisms and relationships between categories
How to ensure exclusivity:
Careful assessment if newly added categories are free of overlap; if needed solit or re-arrange
Reliability
An analysis is reliable when …. are obtained when the study is ….
Under ….
Reliability
An analysis is reliable when THE SAME RESULTS are obtained when the study is REPEATED
Under SIMILAR CIRCUMSTANCES
Quantitative content analysis APPROACH 1 2 3 4 5
Advantage
- Development of research question & hypotheses
- Collection of material
- Develop & Testing of category system
- coding
- analysis & interpretation
Advantage:
+ data that is objective, countable –> statistically testable
Case studies
- focus on underatanding the ….. in ….. cases
- include … or ….. cases and have …… of analysis
- …… methods of data collections, which can be ….. (text) or ….. (numbers)
Used to:
- description of …..
- theory ….
- theory ….
Case studies
- focus on underatanding the DYNAMICS in INDIVIDUAL cases
- include 1 or MORE cases and have MULTIPLE LEVELS of analysis
- MULTIPLE methods of data collections, which can be QUALITATIVE (text) or QUANTITATIVE (numbers)
Used to:
- description of PHENOMENA
- theory DEVELOPING
- theory TESTING
Steps in case study research
- beginning
- case selection
- development of instruments and protocols
- entry into the field
- data analysis
- hypothesis formation
- relating to literature
- finalizing
Step 2 of case study research - case selection
- sample
- Choice of cases
- sample from the population
- cases are selected on theoretical reasons (not random)
- -> to support other cases
- -> provide example of a theoretical construct
–> choose extreme situations and strongly differing cases
