qualitative data analysis - strathmore university€¦ · key components of data analysis mmba 8109...

MBA 8109: Research Methods

Qualitative Data Analysis

Learning outcomes

By the end of this session, you should be able to:

Understand the nature of qualitative data and its implications for analysis.

Identify the main issues to consider when preparing your qualitative data for analysis.

Use some techniques to analyse qualitative data.

Understand the implications of using computer assisted qualitative data analysis software (CAQDAS).

2 MMBA 8109 - Research Methods

Introduction

• Qualitative research involves an array of interpretive methods that are used to describe and translate the different meanings that people ascribe to their experiences.

• It comprises delving deeply into people’s hidden interpretations, understandings and motivations.

MMBA 8109 - Research Methods 3

Introduction

• Qual. Research is designed to inform the researcher how (process) and why (meaning) things happen as they do.

• It aims to achieve an in-depth understanding of a situation e.g. consumer motivation, consumer behaviour, employee perceptions, mentoring relationships.


Qualitative research designs

• Action research (organizational research)

• Case study (in-depth analysis of a single person, event,

process or organization)

• Grounded theory (inductive theory-building)

• Narrative inquiry (interpretive story-telling)

• Ethnography (study of a local culture)

• Phenomenology (study of the lived experience of people

who have faced a common event e.g. retrenchment)


Nature of qualitative data

• Captured in words and images not numbers.

• Involves a study of people in their natural and social contexts.

• Includes many variables to capture the complexity of life.

• Researcher is the chief data collection instrument.

• Focuses on meaning and interpretation of social reality.


Data collection methods

• Qualitative research can involve:

– Focus groups.

– Unstructured or semi-structured interviews.

– Document review of current or archival/historical documents.

– Participant/non-participant observation.

– Examination of cultural artefacts.


How is qualitative data captured?

• Extensive field notes.

• Interview transcripts.

• Photocopies of contextual /archival information.

• Photos, audio and video recordings.

• Community maps (PRA tools).

• Drawings (especially by children).

– QUALITATIVE DATA CAN BE OVERWHELMING!


Building blocks of analysis

• Qualitative data will usually undergo three phases to transform it into a research report.

1. Description – of context, phenomenon, case, individuals.

2. Analysis – systematic approach to derive patterns and themes.

3. Interpretation – researcher’s attempt to derive meaning from the data.

• Involves both inductive and deductive approaches.


Key components of data analysis


Miles, M. B. and Huberman, A. M. (1994) Qualitative Data Analysis: an expanded sourcebook, SAGE Publications Inc.,

Thousand Oaks, California.

Analysis

Data collection

Data reduction

Data display

Drawing conclusions

Data reduction

• Writing summaries – interim/progress summaries; transcript summaries; document summaries.

• Categorizing data (coding).

• Teasing out preliminary patterns and themes.

• Writing researcher memos (research notebook or reflective diary).


Data display

• Visual display of compressed data in a matrix, graph, chart or network.

• Matrices may be ordered around

– Checklists

– Chronological events

– Processes

– Roles of participants

– Concepts


Generic approach to analysis

1. Identify codes/categories that allow you to reduce and understand your data.

2. Attach data from different transcripts and notes to the appropriate codes.

3. Identify key patterns/themes for further exploration.

4. Develop testable propositions.

5. Draw conclusions and verify them.


The QDA Exercise

MPM 8109 - Research Methods 14

1. What categories did you use to reduce your data?

2. What themes did you pick out?

3. What testable propositions would you propose for what makes a successful teacher?

4. What conclusions would you draw?

09/07/2014

The Aliko Dangote Interview


1. How did you reduce your data?

– How did you organize your notes?

2. What themes did you pick out?

3. What testable propositions would you propose for what makes a successful entrepreneur?

4. What conclusions would you draw?

Developing testable propositions

• Important to test the propositions that emerge inductively from the data to strengthen the validity of your conclusions.

• How? Seek alternative explanations and negative examples that do not conform to the patterns/themes being explored e.g. minority views.


Verifying conclusions

1. Check for “majority views” that represent the sample – get feedback from participants.

2. Check for researcher biases.

3. Triangulate the evidence (use different sources)

4. Consider outliers/extreme cases.

5. Consider rival explanations (building theory).

6. Rule out spurious relations (building theory).


Addressing research quality

1. Credibility (Internal validity): accuracy & truthfulness of results or findings.

2. Confirmability (Objectivity): freedom from bias.

3. Dependability (Reliability): consistency of results or findings (audit trail)

4. Transferability (External validity): extent to which findings are generalizable to a population or different context.


Questions to ask

1. How do you know you have produced an “accurate” account?

2. Have you conveyed meaning that helps readers deepen their understanding of an issue or phenomenon?

3. By whose standards is the account valid? The researcher, the participants, or the readers?

4. How can we evaluate the quality of qualitative research?

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Validation Strategies in Qualitative Research

1. Prolonged engagement and persistent observation in the field.

2. Triangulation of data, methods, investigators and theories.

3. Peer review (devil’s advocate).

4. Member checks (participant debriefing)

5. Negative case analysis (form of verifying conclusions).

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Validation Strategies in Qualitative Research

6. Clarifying researcher bias (being explicit about past experiences, prejudices and orientation).

7. Providing a rich thick description (details).

8. External audits of both process and product.

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Reporting the findings


• Quantitative studies use a combination of charts, tables and statistics to present the results from survey questionnaires.

• Qualitative studies provide contextual descriptions, narratives and interpretative analyses supported by quotations.

• Avoid using your report as a dumping ground for quotes!! Be selective.

Choosing a CAQDAS package


1. How much qualitative data do you have?

2. How important are these data in relation to other data collected for your research project?

3. How much time do you have to learn how to use the package?

4. Is there technical support available?

5. Can you afford the cost of the package?

Selected CAQDAS Websites


• ATLAS.ti – www.atlasti.de

• HyperRESEARCH – www.researchware.com

• Nvivo – www.qsrinternational.com

• QSR N6 – www.qsrinternational.com

http://www.atlasti.de/

http://www.researchware.com/

http://www.qsrinternational.com/

http://www.qsrinternational.com/

qualitative data analysis - strathmore university€¦ · key components of data analysis mmba 8109...

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