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Explaining the Types of Qualitative Analysis Methods

written by: N Nayab • edited by: Jean Scheid • updated: 5/26/2011

Qualitative research is a method of inquiry that finds widespread employment in social sciences, market research and other areas. Read on for some of the popular qualitative methods of data analysis.

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    Qualitative Method of Data Analysis Qualitative Analysis aims at securing an in depth understanding or the “why" and “how" of human behavior and decision making, over “what," “when" and “where." It produces specific information on the cases studied rather than general conclusions and is used to gain support for research hypothesis.

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    Case Study

    Case studies are the most popular qualitative methods of data analysis.

    A case study method focuses on the in depth study of a single, usually complex series of events, that make up a case. The study focuses on all aspects and dimensions of the case in question, aimed at illustrating viewpoints or theories rather than making comparisons. Even when conducting a series of case studies, comparisons between two or more cases would remain faulty, as each case study has a specific design which need not necessary remain suitable for making comparisons.

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    Action Research

    Another popular qualitative data analysis method is action research. As the name suggests, action research is research through actions. It is a systematic and interactive inquiry process that involves a three step cyclical process of and fact-finding or examining the practices for improvements, planning for improvements, and implementing new practices or taking action.

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    Analytic Induction

    Analytic induction is the progressive redefinition of a concept by collecting data, developing analysis, and organizing the findings to construct and testing causal links between events and actions.

    The methodology of analytical induction is inspecting initial cases to identify common factors and the seek explanation for existing linkages, and reworking the explanations based on the findings from new cases. Success depends on testing cases with new varieties of data to validate or revise established linkages, until negative cases cease to exist.

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    Ethnography is the study of people in their natural settings to capture their ordinary and normal activities. It focuses on capturing the values, ideas, and material practices articulated by the subject.

    There is no rigid method or process for ethnography, and the tools include other multi-method qualitative tools, such as:

    1. Field Research - The observation of any normal every day event in the environment where it occurs.
    2. Ethnomethodology - Defining and interpreting everyday life through people’s talk and interactions. A related branch is conversation analysis, or fine-grained analysis of natural talk based interactions to construct patterns of social order.
    3. Discourse Analysis - Language and literature is a reflection of the world around the writer, and discourse analysis is the study of the world, society, events and psyche as represented in language and discourse. The forms of discourse analysis include semiotics, deconstruction and narrative analysis.
    4. Biographical Research - The analysis of a person’s written account or narrative, usually the life history, trying to identify the epiphany or turning point
    5. Interviews - Direct interview of the subject or people closely associated with subject, on life history.
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    Comparative Analysis

    Qualitative Method of Data Analysis Comparative analysis involves analyzing data from different settings or groups, but belonging to the same point in time and/or the same settings, to identify similarities and differences.

    Two qualitative methods of data analysis of a comparative analysis nature are matrix analysis and constant comparison.

    Matrix analysis or logical analysis involves categorization and arranging collected data in flow charts, tables, diagrams and other forms of representation to represent the cause and process in a tabular, pictorial or graphical manner. This approach helps make comparisons and in construction of hypothesis.

    Constant comparison is comparing new data with previously collected data coding the same to develop theoretical categories.

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    Frame Analysis

    Frame analysis is rooted in psychiatry and psychology, and explains social phenomena through symbolic-interpretive constructs or frames that people adopt in their normal daily lives. Examples of such frames include beliefs systems, social convictions, phobias, norms and more. The frames people adopt depend largely on the society they live in.

    Framework analysis is the classification and organization of data based on key themes or concepts, with matrix based subdivisions that illustrate connections between different frames.

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    Grounded Theory

    Grounded theory involves the simultaneous collection and analysis of data, usually through observations. This approach develops the theory from the data collected rather than trying to test whether the collected data fits any preconceived theory. The researcher reads the text or data collected to identify theoretical and analytical codes. A central part of this exercise is constant comparison, or checking to see if the new data remains consistent with previously collected data.

    One approach to grounded theory is line by line coding, where the researcher codes each line of the data collected instantly, such as accepts what the interviewee says point blank without the chance of being influenced by preconceived notions that may creep up if the analysis is left for a later stage.

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    Interpretative Phenomenological Analysis

    Interpretative Phenomenological Analysis (IPA) is an approach wherein the researcher understands the experiences of participants the way participants themselves understand, rather than trying to analyze an objective record of the experience.

    IPA takes place through semi-structured interviews, and through diaries and other personal accounts. The data collected from such methods is subject to analysis to identify the key themes verbatim.

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    Objective Hermeneutics

    Objective hermeneutics is a method of interpreting textual data where a team of researchers develops different interpretations and mutually criticizes such interpretations to modify or exclude such interpretations. The initial interpretations are preliminary hypotheses and further criticisms are validating or disapproval of such hypothesis using further empirical material.

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    There are many more qualitative methods of data analysis, and the list above denotes only some of the more popular methods. Regardless of the methodology used, success in qualitative research depends on selecting a small but focused sample.

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    1. Online QDA. “Methodologies." Retrieved April 21, 2011.
    2. Ratcliff, Donald. “15 Methods of Data Analysis in Qualitative Research." April 21, 2011
    3. John V. Seidel. Qualitative Data Analysis. retrieved April 21, 2011.

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