Qualitative Secondary Data Analysis
The same data set can be primary data for one researcher and secondary data for another.
Advantages
No need for new data collection
Cheaper
Supports data-driven decision-making (you can see where the data gaps are more easily)
Time comparisons
Scope and variety of the data available
DIsadvantages
No discretion over the types of data collected or methods used
Potential risk to quality
Not always possible to get clarification on issues
Might not answer the question
Different sorts of classification
Steps for succedssful secondary analysis
Develop the research question
Identify the data set
Evaluate the data set
Define the scope of the data set
Evaluating data
What were the agency’s or researcher’s goals in collecting the data
What data were collected, and what were they intended to measure?
When was the information collected?
What methods were used for data collection? Who was responsible and what were their qualifications? Are they available to answer questions about the data?
How is the information organised? Are there identifiers used to identify different
types of data available?What is known about the success of the data collection effort? How are missing data indicated and treated? What kind of documentation is available?
How consistent are the data with data available from other sources?
Qualitative secondary analysis (QSA)
(Re)contextualisation — The context of the data; how these data are of their time and place
(Re)connection — How the data might be used now, beyond the ‘original‘ context
Process of QSA — Quesitonning
Descriptive – what is happening?
Causal – why is this happening?
Processual – how is this happening?
Temporal – when is this happening?
Spatial – where is this happening?
Locative – who is this happening to?
How do children and adolescents in Sub-Saharan Africa use cultural icons in their drawings to represent and make sense of their experiences of conflict?
How are symbols of conflict and peace represented in the drawings of children and adolescents in Sub-Saharan Africa, and what role do cultural icons play in these visual narratives?
What do the drawings of young people in conflict-affected areas of Sub-Saharan Africa reveal about their perceptions of identity, resilience, and hope, particularly through representations of cultural icons?
Use search terms to identify the right repository and dataset
Order and group your cases. Some cases will seem to group together
‘naturally’. Consider why this might be in relation to your own analytical interests.Which questions can be supported by these cases?
What might you not be seeing because of your approach?
Process of QSA — Refining your questions
How do children and adolescents in Sub-Saharan Africa use cultural icons in their drawings to represent and make sense of their experiences of peace conflict?
How are symbols of conflict and peace represented in the drawings of children and adolescents in Sub-Saharan Africa, and what role do cultural icons play in these visual narratives?
What do the drawings of young people in conflict-affected areas of Sub-Saharan Africa reveal about their perceptions of identity, resilience, and hope, particularly through representations of cultural icons?
Process of QSA — Reflecting
Reflect on doing this process and think about the next steps:
How did you find this process?
What was helpful?
What was difficult?
What are you still unsure about?
What do you think you need to do next?
Processes of QSA: Getting to know the data
Immerse yourself: read, review and listen to all the materials repeatedly.
Note relationship between visual, written and spoken data
Keep participant explanations close — analysis begins with their words/talk
Create analytic memos to capture first impressions and reflexive notes
Processes of QSA: Avoiding fractured analysis
Always ‘marry up’ what participants drew, wrote, and/or said.
Do not interpret drawings without accompanying talk/text.
Consider contradictions across modes as analytically meaningful.
Ask: what happens when I read image and words together?
Processes of QSA: Deciding your analytic lens
Choose approaches suited to your research question:
Coding/Thematic – pattern-finding.
Holistic – overall composition and feeling.
Semiotic – signs and symbols.
Phenomenological – experience and emotion.
Discourse/Narrative – language, story, and power.
Processes of QSA: Coding the data
Break data into meaningful segments (visual and verbal).
Develop shared or co-created codes with another analyst
Example: 'peace,' 'violence,' 'community,' 'healing' across image and text.
Keep an audit trail linking each code to participant explanation
Processes of QSA: Categorising and mapping
Group related codes into categories or patterns:
Temporal (change over time)
Spatial (places, movement)
Networked (relationships, connections)
Cultural/Symbolic (shared meanings)
Visualise categories using matrices or thematic maps
Processes of QSA: Moving from description to interpretation
Treat each mode (drawing, writing, talking) as a conversation partner.
Integration strategies:
Mosaic analysis: layer insights from each mode.
Conversational analysis: themes 'speak' across datasets.
DNA model: weave interpretations iteratively for richer meaning.
Ask: what does each mode add or challenge?
Identify where codes and categories converge or diverge.
Build interpretations grounded in participant meanings
Test insights against original data and theory
Use participant quotes, visuals, and excerpts as evidence.
Summary
You now know the difference between primary and secondary data. You also understand the advantages and disadvantages of secondary data and its analysis.
You know the steps to take to carry out secondary analysis with qualitative data.
You understand that secondary analysis brings specific ethical challenges