Qualitative research - data analysis Flashcards
1
Q
What is the purpose of qualitative data analysis?
A
- long transcriptions and recorded field notes - data needs to be reduced and have order imposed
1. DESCRIBE
2. DEVELOP THEORY
3. DEVELOP HYPOTHESES - for other research
2
Q
What is meant by ‘all data analysis is data reduction’?
A
- schemes for reducing data - developed during and after data collection
- during = concurrent data analysis
- GT = constant comparative analysis to develop hypotheses + test them out at subsequent interviews
3
Q
How are qualitative data analysed?
A
- quantification (counting - e.g. count no. of times something is said or individuals contribute)
- Thematic content analysis
- Framework analysis
- Transparent analysis
4
Q
Should qualitative researchers quantify?
A
- some would say no
- BUT useful for esuring researcher focuses on what is really in the data
- can encourage rigour and honesty
- can be useful to do some quasi (counting) when reporting findings using language such as ‘all’ ‘some’ of the PPs said…
5
Q
Challenges for qualitative researchers?
A
- no rules for data analysis
- no statistical packages to do data analysis for you
- makes qual. data analysis difficult to describe
- have to make sense of loads of data
- interviews often 90 mins
- labour intensive
- presentation = tricky
- if yyou reduce qual. data too much = sense lost and meaningless
6
Q
Transparent analysis?
A
data analysis does need to be reasonably transparent
7
Q
What are the stages of data analysis?
A
- tidy up data
- check transcription against recording
- develop method to index the materials so they are easily accessible
- commonly enter the data into a qualitative data analysis programme e.g. NVivo, Atlas ti - help to organise data and clarify thinking
8
Q
What is thematic content analysis?
A
- go through transcript looking for themes (things that crop up over and over)
- ‘commonalities’ emerge from data
- themes = given a code (word/phrase)
- codes then collapsed in to categories
- constantly reducing data –> more manageable/meaningful
- looking for variation within data
9
Q
What is framework analysis?
A
- take a framework to the data and put it into categories
- framework can come from pre-existing theory or initial thematic analysis
10
Q
What happens when data is interrogated?
A
- do themes apply in certain sub-groups?
e. g. males, mature students - analysis of negative cases
11
Q
How do researchers check/validate their analyses?
A
- if more than one researcher - all analyse and then compare
- can also present analyses back to PPs
- member checking - but analysis is interpretive (no right or wrong)
12
Q
What are the final stages of data analysis?
A
- interelate the themes - so creates an integrated whole/ tells a story
- difficult process - qual. data analysis packages can help e.g. diagramming - but ultimately relies on creativity and intellectual rigour of researcher
13
Q
How is the data presented?
A
- in a paper - logical journey through the data is presented under a no. of themes
- typically as quotes followed by some analysis
- easier to present qual. findings in a book
- lengthy quotes, followed by clear analysis and interpretation = good way