Analyzing & evaluating Analyzing & evaluating qualitative dataqualitative data
Kim McDonoughNorthern Arizona University
Epistemology in qualitative Epistemology in qualitative researchresearchTheory of knowledge
◦Constructionist—Meaning/knowledge vary across people and over time
◦Holistic—complex topic is viewed from multiple perspectives
◦Subjectivist–Knowledge/meaning is personal
◦Context-based—Knowledge is negotiated socially and historically
Search for knowledge◦Truth is relative & context specific◦Goal is interpret how people
construct meaning◦Start with experiences and build
theory inductively ◦Data provides information that must
be interpreted◦Interpretation is shaped by the
researcher’s own experiences
““Good” qualitative Good” qualitative researchresearchMaintains a single focus/idea/problemUses rigorous data collection
◦Sufficient time in the field◦Many sources from multiple perspectives◦Detailed summary of each source
Employs rigorous data analysis◦Multiple levels of abstraction◦Verification of the accuracy of the findings
Engaging report◦Clear, detailed writing◦Accurately reflexes complexity of the context
Appropriate topics for Appropriate topics for qualitative researchqualitative researchThe research question asks how or
what◦Focus on understanding
The topic needs to be explored◦Theory doesn’t exist yet, is
insufficient, or hasn’t been tested in a particular context
◦The small pieces that make up the big picture haven’t been identified yet
◦Time & resources are available ◦A receptive audience exists
The natural setting is the focus of inquiry◦Obtain information from participants
in their natural environment◦Reveal contextualized
patterns/truthsThe researcher’s interests
◦Take a personal role in the project◦Serve as a voice for the participants
Basic tenets of qualitative Basic tenets of qualitative analysisanalysisThe search for patterns in data
and ideas that help explain the existence of those patterns
The goal◦Reduce huge amounts of text to
manageable units for further analysis◦Interpret the contribution of those
manageable units to existing knowledge or practice
Steps in data analysisSteps in data analysisPreliminary steps: Organize the data
◦Organize the data◦Label/identify source of the data◦Convert to appropriate text units if
necessary◦Enter any numeric information into
spreadsheet◦Determine which data sources are
available for each participant◦Make decisions about inclusion or
exclusion criteria based on completeness of data
Form general impressions◦Read all the data multiple times
Do not analyze each data source separately
Do not prioritize one source of data over another
◦Get a sense of the whole before trying to break it into parts
◦Make notes—short phrases, ideas, or key concepts
Analysis: Form initial categories◦Search for categories, themes, or
dimensions◦Identify & name the major themes◦Describe each of the themes◦Check descriptions to refine
overlapping categories
Classify data segments by themes◦Read the entire data set again◦Identify segments in all sources that
belong to each theme◦Keep track of segments that don’t fit
with a theme
Evaluation: Assess themes & segment assignment◦Evaluate whether the themes are
appropriate in light of all the segments
◦Decide if all the segments fit with an existing theme
◦Rename/combine/separate themes if necessary
◦Create new themes if necessary
Interpretation◦Make sense of the patterns in the data◦Step back from the summarizing the
data and find links to larger meaning Based on insights/intuition/hunches Based on an existing construct, idea,
theory, practice Based on similarity/divergence from
previous research findings
Verifying accuracy in Verifying accuracy in qualitative data analysisqualitative data analysisProlonged engagement/persistent
observation/time on site◦Building trust with participants, learning
the culture, checking misinformation and distortions, time on site
Triangulation/Diversity of method◦Use multiple sources, methods,
investigators◦Elicit multiple perspectives◦Identify corroborating evidence from
multiple sources
Clarifying researcher bias◦State past experiences, biases,
prejudices & orientations that may have shaped the inquiry & interpretation
Peer review/debriefing◦An external check of the
research process◦“The devil’s advocate”
Member checks◦Solicit the informants’ views about the
credibility of the findingsExternal audits
◦Someone with no connection to the study
◦Allow an external auditor to examine the process and product of analysis
◦Determines whether the findings, interpretations, conclusion are supported by the data
Rich, thick description◦Describe in detail and participants
and the setting◦Allows readers to make decisions
about transferabilityNegative case analysis
◦Refines working hypotheses as data analysis/interpretation unfolds
◦Revise hypotheses until all cases fit◦Account for outliers and exceptions
Deciding which techniques to use◦Use at least two (Creswell)◦Easiest, cost-efficient, most popular
procedures Triangulation Rich, thick description Member check
DiscussionDiscussionProcedures you have used for
verifying evaluation◦Successful ones?◦Challenges or concerns?
Current qualitative projects?Suggestions for data sources &
perspectives?