Numerous data analysis methods exist. The choice of method must fit the research design, for example analysis of the transcribed text for meaning with the view of finding themes or the interpretation of actions to derive meaning. Other methods could focus on the discovery of patterns, or typologies, or categories through constant comparison, matrices or charting. Further methods include reflective or metaphorical analysis. Don Ratcliff provides an oversimplified (in his opinion) listing of 15 methods (Download 15methods his descriptors):
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Typology |
Classification system derived from patterns, themes, or other kinds of groups of data. Categories should be mutually exclusive. |
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Content analysis (considered a specific form of typology) |
Analysis of documents, text, or speech for emerging themes and find how themes relate. Start by reading through for holistic view and then specify rules. Determine categories and frequency to find latent emphasis. |
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Discourse analysis |
It is a linguistic analysis of several people conversing. Find patterns of interaction, domination by who, duration and how. |
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Narrative Analysis |
Study an individual's speech, the story a person shares about self. Consider the core plot in the story, the context-situation and basic actions. Could involve study of diaries or folklore or literature. |
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Phenomenology |
A heuristic analysis of how individuals experience the world. It emphasizes idiosyncratic meaning to individuals. Bracket self out and enter into the other person's perspective and experience |
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Hermeneutical Analysis (hermeneutics = making sense of a written text) |
Not looking for objective meaning of text, but meaning of text for people in situation— use their words. Use context—time and place of writing, the cultural and historical context—to understand. |
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Semiotics |
Determine the meanings of signs and symbols, such as body language, also social construction from influence of others (symbolic interactionism). |
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Metaphorical Analysis |
Try various metaphors and see how well they fit and check validity of metaphor with participants or ask participant for metaphors. |
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Quasi-statistics |
Use enumeration (count) to provide evidence for categories created, based on the frequency something is mentioned in field notes. |
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Event Analysis/Microanalysis |
Finding precise beginnings and endings of events—the boundaries, then find phases in event by repeated viewing. |
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Logical/Matrix Analysis |
An outline of generalized causation by using flow charts, diagrams, etc. to pictorially represent. |
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Analytic Induction |
Consider an event and develop a hypothetical statement of what happened. Look for a similar event and see if it fits the hypothesis. If it doesn't, revise hypothesis. Look for exceptions to hypothesis, when find it, revise hypothesis to fit all examples. |
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Domain Analysis |
Analysis of language of people in a context and description of social situation and meaning of cultural patterns within it—semantic relationships. Folk, mixed and analytic domains. Worksheet and samples from field notes, formulate questions about relationships. |
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Taxonomy |
Often used with Domain Analysis in developing a taxonomy from a single domain. Sophisticated typology of super-ordinate and subordinate categories |
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Grounded Theory |
Constant Comparison—look for indicators of categories in events and behaviour, name them and code them on document. Compare codes to find consistencies and differences. Consistencies between codes—similar meanings or pointing to a basic idea—reveals categories, eventually category saturates. Memo on the comparisons and emerging categories. Certain categories become more central focus—axial categories. |
