The Analysis of Qualitative Data Jane F. Gilgun University of Minnesota, Twin Cities March 2004 Revised March 2007

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1 The Analysis of Qualitative Data Jane F. Gilgun University of Minnesota, Twin Cities March 2004 Revised March 2007 Learning how to analyze qualitative data is on-going. Those who are just beginning and those who have been doing it for decades are still learning. We learn how to do analysis by doing it, by consulting what others have done it, and by discussing our work with others. Preliminary Studies In doing qualitative research, I recommend that researchers do preliminary studies in order to find a focus. Once you have a focus, you can then do a literature review, see whether your focus can contribute to what is already known, and go on to develop research questions, hypotheses if you want to test hypotheses, and definitions of core concepts. This is important to do for proposal writing. Most research begins with a proposal, which is a research plan. Researchers also are likely to want to do preliminary studies if they are doing research on how programs work, sometimes called developing a theory of change. In many kinds of evaluations, evaluators begin their work in an open-ended way in order to identify what might be of interest and importance to the stakeholders of the evaluation. The following are sensitizing guidelines for the conduct of analysis. This discussion is not meant to be definitive, but provides suggestions about analysis. I will revise these notes from time to time. These guidelines apply to doing preliminary studies and studies that are a bit further along and have focused research questions and hypotheses. Transcriptions In transcribing interviews, I recommend verbatim transcription that involves including the ums and ahs and counting the number of seconds the pauses last. These details can be important cues about informants states of mind and your own. For example, after a particularly startling statement by one of my informants, I was silent for about 13 seconds. That is a long time in an interview. Sometimes informants are silent for a long time. Silence can be significant, too. With a limited budget, some researchers only transcribe parts of the tapes they think are relevant to the purpose of focus of their research. With this said, I recommend that scholars listen to the tapes several times before they conclude that their analysis is complete. In that way, they can check to see if they missed anything that did not seem important at the time the partial transcription was done. On are occasions, interviewees are reluctant to be tape recorded. This must be respected. However, check to see if they would permit taping if you erase references to names and any

2 Page 2 of 9 other information that could be identify them. If not, then immediately after the interview, tape record your recollections of what the interviewee said in the interview and any other relevant details. During the interview, take detailed notes. Expand upon them immediately after the interview using the format that follows below. If the interviewee does not want you to take notes during the interview, then respect that, but, again, write up your notes right after the interview using the format below. Fieldnotes Whether you do observations, interviews, or document analysis, I recommend fieldnotes. In fact, in some observational studies fieldnotes could be your only data, although many field researchers using observations also do interviews and even document analysis. When doing interviews and document analysis, fieldnotes are invaluable. They are a wonderful source of ideas and can provide a good accounting of what went on during the interview. In fieldnotes, you record your subjective reactions, any thoughts about analysis and links to related research and theory, and describe non-verbal responses that informants have and that are impossible to capture on audiotape, such as facial expressions and shifts in intensity in your sense of connection to informants. In writing fieldnotes, you often come up with new insights and new directions that you might want to pursue. Writing is a great way of finding out what you are thinking. A useful way to organize fieldnotes is to have four sections: 1) Preliminaries: a careful description of the setting, who was present, description of interviewee and/or persons observed, and diagrams of the settings and of any movements that may have occurred among the participants in the setting, when this is relevant to the research questions. 2) Descriptive text: a section on descriptions of what happened, who said what, the nonverbals, the tones of voice, and any other relevant detail. 3) Observer comments (O.C.): a place for researchers to record their emotional reactions, their doubts, fears, and concerns. These can be placed in the midst of the text of the descriptions and labeled Comments. Some reflections and quick thoughts about applications, comparisons to what you ve found in other interviews/settings/observations, and linkages to related research and theory can be made here. 4) Memos: a section at the end of the fieldnotes where researchers record their reflections in a more leisurely way. They can reflect on what they observed in their interviews/observations, think about what else they might want to know, think about research and theory that is relevant to what they are learning, the scholarship that the findings might contribute to, and comparisons across cases, among many other topics. Often in memos, researchers reflect upon emerging ideas and concepts that are of interest to them and/or seem important to understand the phenomena. Bogdan & Biklen (2006) have an excellent discussion of fieldnotes. I have found field notes to be important in data analysis and in writing up the findings. More than one of my

3 Page 3 of 9 articles was based primarily on field notes ( Gendering Violence and Fingernails Painted Red. ) On-Going Analysis While conducting interviews, observations, or document analysis, you will naturally be analyzing what you are hearing and seeing. More or less automatically, you will be classifying what you are learning in informal ways, based on your store of general knowledge that includes knowledge of research and theory and personal and professional experience. You also are likely to be linking what you are seeing and classifying to research and theory and perhaps to professional and personal experience. If you began your study with hypotheses and/or research questions, you will have them in mind. You will test the hypotheses the sense that you want to see how they hold up as you conduct interviews, observe, read documents, and do the analysis. You also will be changing these hypotheses in light of your on-going interpretations. Furthermore, you will be identifying dimensions of the concepts that compose the hypotheses. You can think of hypotheses in various ways, but I think of them as preliminary statements about the relationships among variables. Whether you are doing deductive qualitative analysis (DQA) (Gilgun, 2005) that involves both hypothesis testing and hypothesis development or searching for a focus for a study whose goal is theory development, you will add to, undermine, or transform your hypotheses and the concepts that compose them over the course of analysis. If you are not seeking to develop theory, you will not be working with hypotheses but with research questions that you want to answer. A question I have had was what does violence mean to perpetrators. I didn t know what it did mean so the question made sense to me. Over the course of interviewing perpetrators, I began with wondering what child molestation mean to child molesters. When I had a pretty good sense of that, I pursued the question of what rape means to men who have raped. I moved to several other different forms of violence. I might have reformulated my research question along the way into hypotheses, but I actually wanted descriptive information and did not want to build theory. Now that I am near the end of the research on violence, I probably do have a theory of the meanings of interpersonal violence to perpetrators, but my primary goal has been descriptive and for me to understand what violence means to perpetrators. The processes are pretty much the same whether you are doing preliminary studies, seeking to develop theory through hypothesis development, or whether you are seeking descriptive information for the purposes of understanding a social phenomenon. Solo or Group Analysis of Data? The ideal is to have at least one other person to talk with about emerging findings, including having that persons read your fieldnotes and discuss them with you. You can edit out

4 Page 4 of 9 any personal information that you prefer not share. Sometimes it is helpful to have at least one other person read and code your transcripts with you. The synergy that results can greatly enhance your understandings and your analysis. Talking to another knowledgeable person will bring out some of your own insights. The other person will have perspectives different from your own that may spark new thinking and lines of inquiry in your project. Also, another person may challenge how you are thinking about your analysis that will result in perhaps a more in-depth analysis. Working with another person can also help you sort our emotions and memories that interviews may activate in you. Processing emotions and memories can lead to greater insight and perhaps even deepened capacities to understand what informants are saying to you (Gilgun, 2007). Besides, group analysis of data is a term that goes way back, at least to Booth s (1903) studies of the London poor at the end of the nineteenth century. My preference is to keep qualitative approaches rooted in their scholarly traditions. Treating Each Interview as a Pilot If you write fieldnotes after each interview, observation, or session perusing documents and talk to a co-researcher, you may find reasons to tinker with your approach to the next informant, such as asking for elaborations or clarifications regarding something the informant had said in an earlier interview, as well as modifying how your interact with informants, such as how you ask questions and how you respond to what informants say. You can evaluate your interview protocol and your interview style as you go along and thus modify your approach. Coding Coding is part of how qualitative researchers do the analysis. Coding involves sorting, categorizing, and organizing the meaning units that researchers identify in transcripts, fieldnotes, and documents. Codes are the names that researchers give to these meaning units. The names researchers chose can come from research and theory, from their professional and personal experience, from the words that informants use, such in studies of mothers and newborns, where the mothers classify their own infants as easy, cranky, or colicky. Strauss and Corbin (1998) describe three types of coding. One is open coding. The scope of opening coding depends upon what kind of research you are doing and for what purposes. If you are doing preliminary work for the purpose of finding a focus, they you can sweep through the transcripts and/or fieldnotes marking up the text with any notation that comes to mind. Coding of existing documents is more challenging until you have them in writeable files or have copies of them, but somehow you have to figure how to organize the meaning units in documents, too. Opening coding is of high importance in preliminary studies. Through being as open as you can be to what informants are telling you, you may identify something interesting and

5 Page 5 of 9 important and eventually chose this aspect of the phenomenon you are looking at as the focus of your study. After you have your focus and collect more data, your coding is likely to be a bit less open and narrow to coding only for the units of meaning that are relevant to your focus. Even after you have chosen a focus, however, though you want to code for the focus, you may want to continue open coding as well, in case you identify something else that is relevant to your interests. When you begin with hypotheses and research questions, you already have a focus. In fact, your interview questions may be more focused than they would be in preliminary studies. With DQA and other approaches that begin with a conceptual framework however tightly or loosely framed, you will have concepts of interest that you will want to code for. You can call these concepts sensitizing because they alert researchers to what could be important given the focus of their research. For example, suppose a researcher uses social information processing theory as a conceptual framework to do research on children and their families where the children are showing antisocial behaviors. The researcher would code the transcript using concepts from social information processing theory. At the same time, however, the researcher might otherwise do open coding in order to identify other aspects of social information processing theory such as the contexts in which children use one attributional style or another. In coding, you can write the codes either within the computer files or you can write them on printed transcripts. Some researchers do computer-assisted coding, using either specialized coding software or word processing programs. The important point about computer-assisted analysis is the ease of locating codes within the text and/or coded segments of texts. If coding on the printed transcripts, it s a good idea to have narrow columns and leave about half of the page blank so you can write your codes next to the segments you are coding. The second type they call axial which means you are relating codes to each other. Think of what an axis is where two or more lines meet and that is the sense of axial coding where two or more concepts are linked. In the Strauss version of coding (Strauss & Corbin, 1998), researchers are encouraged to connect codes through their own coding paradigm which is arranging the codes according to conditions, context, action/interactional strategies and consequences (p. 96). You don t have to use this approach but it does provide one kind of structure. In most research projects, axial coding simply happens. I did it for years automatically before Strauss (1987) wrote about this kind of coding and gave it a name. The third type is selective coding. This means you have identified concepts that become central or core to you analysis. You have amassed enough evidence in the form of coded excerpts to argue for the centrality of the concept. Once you think you have such a concept, then you go back to your transcripts or other documents and code once again, this time to find instances that might add further aspects or dimensions to your codes. You thus are

6 Page 6 of 9 dimensionalizing your codes. For example, a core concept for one of my studies is what violence means to perpetrators. I dimensionalized that concept by identifying in the transcripts the many different meanings that informants gave to their violent behaviors. I thus identified many different aspects or dimensions of what violence means to perpetrators. Sources of Codes What do you think the sources of your codes will be? This often is an unstated issue in qualitative research. Many researchers think they should enter the field with no pre-conceptions and the codes will somehow emerge from the analysis of the data. Many people think this is what induction is, but I think it s naïve empiricism. We bring with us our own frames of reference and these frames influence what we notice and what we don t and how we interpret what we notice. These frames of reference can be outside of our awareness. Glaser and Strauss (1967) recognized that researchers are not blank slates but do indeed bring ideas with them into research. So, in terms of codes, I think in many instances researchers would be more open about their process if they developed a set of codes and defined them before doing any data collection. They will identity new codes and aspects (e.g., dimensions) of codes they hadn t anticipated when they collect data and do the analysis. There is a strong philosophical background to my point of view. As Popper (1969) pointed out eloquently, there is no such thing as induction. We bring out assumptions, perspectives, beliefs, and values with us. Because we do, we operate as deductive human beings, not inductive. There is no such thing as an immaculate concept (Van Maanen, 1998), perhaps echoing Glaser (1978), who said, Immaculate conceptions are not necessary (p. 8). In other words, all of our observations have an overlay of our own thinking, perceptions, etc. So, we can t really enter the field without ideas that will help us identify and categorize what we will notice. our questions. With that said, researchers can make serious efforts to put aside their own ideas and to open themselves up to the ideas and experiences of informants. We can carefully examine and account for our own prior ideas. We can talk to others about our prior ideas and then process with other people what we are learning from informants. Our purposes for doing so is to develop skills in drawing out other people and putting our own thinking aside in order to understand and hear what informants are telling us. Writing out your Assumptions Before Collecting Data Because we really operate from prior assumptions You can call them internal working models, cognitive schemas, scripts, etc.. I think it is important to write down our assumptions before we enter the field. So, to be reflective, aware researchers, it s helpful to write out assumptions, perspectives, beliefs, values, emotions, and hunches about the topic you will be

7 Page 7 of 9 researching. Based on your prior knowledge of the issues related to your prior professional and personal experience, you probably have many ideas already. It is important to explore our prior ideas and experiences related to the general area we wish to research for a couple of reasons. First, it moves you away from naive empiricism that is characterized by researchers inattention to their personal perspectives and their often unexamined assumptions that their personal perspectives are unrelated to the research they are conducting when actually assumptions are inseparable. Second, doing this may make you more able to hear informants points of view more clearly. If we have an awareness of our own assumptions, we can put some restraints on them. Then, we are more likely to allow other points of view to refute our own. Third, you may arrive at some terrific hypotheses to test and some important sensitizing concepts that will guide your research. Hypotheses and Sensitizing Concepts Think about whether you might be testing hypotheses, testing hypothesized patterns of relationships, seeking to answer research questions and develop descriptions of human phenomena, and using sensitizing concepts or not. Your decision will influence how you analyze data. I really is ok to test hypotheses in qualitative research. In fact, it often is more honest to be explicit about the hypotheses we are testing. Sometimes we have patterns of expectations and not hypotheses in the classical sense. These can be written out so that readers will know what you are testing. Testing hypotheses and testing presumed patterns in qualitative research is usually done once case at a time, where researchers write out the hypotheses or the patterns they expect, test them on you re the first case. Then, they change their hypotheses/patterns to fit case 1. They test the revised framework on the next case and change the framework to fit case 2. And so on. This is a fundamental process in any qualitative research whose goal is theory development. Sensitizing concepts (Blumer, 1986) give direction to researchers. They alert researchers to some important aspects of research situations, though they also may direct attention away from other important aspects. Research usually begins with such concepts, whether researchers state this or not and whether they are aware of them or not. Concepts from the hypotheses, from the patterns that have been hypotheses, and from the sensitizing concepts form a set of pre-established codes that you identify and define before you collect data and analyze it. You may have reason to change the codes over the course of the research, as you would any other part of the design. You may be wondering if unexpected findings can emerge if you begin your

8 Page 8 of 9 fieldwork with prior frameworks. Yes, they can. A purpose of qualitative research is the construction (not the discovery) of new understandings. Researchers consciously try to refute their hypotheses, frameworks, and concepts that they think are central. That is, they purposefully seek information that will contradict what they have assumed and what they have found so far through their research. They are doing the research in order to arrive at deeper fuller understandings and by having this as a goal they therefore will end up with hypotheses, other frameworks, and concepts that could be quite different from what they expected, or they could end up with material that at least have been changed to better reflect what informants state to be their experiences. Organization of Findings While thinking about data analysis, it is important to think about how you will present your findings in research reports. Usually the revised/new concepts, hypotheses, and patterns of relationships provide the organizing framework. Diagramming your findings can be helpful, too. Using concepts, hypotheses, and patterns to organize. After stating what the findings are, researchers provide their interpretations and excerpts from the interviews. The excerpts provide some evidence for interpretations as well as to illustrate the conceptual findings. Also in this section, researchers link their findings to related research and theory. This linking is important to do, especially in qualitative research because our findings may be quite different from what has come before and anything we can do to show how what we finds fits and/or changes other research and theory will help readers understand our findings. Besides, doing this simply is good scholarship. Diagrams. Schematics can be terrific ways of showing your findings, especially if there are multiple pathways and/or multiple outcomes to processes. I think your project involves processes and I would expect that even with a sample of five you will find more than one process at work. Summary Data analysis in qualitative research is a multi-faceted endeavor. It requires a planning, an appreciation of the provisional nature of human knowledge, capacities for being open to views that are different from our own, strong conceptual skills, and excellent scholarship. Analysis can take a long time to learn. Much of the learning takes place as researcher do the research. References Benner, Patricia (Ed.) (1994). Interpretive phenomenology. Thousand Oaks, CA:

9 Page 9 of 9 Sage. Bogdan, Robert & Sari Knopp Biklen (2006). Qualitative research methods for education (5th ed.). Boston: Allyn & Bacon. Booth, C. (1903). Life and labour of the people in London. Final volume. London and New York: Macmillan. Blumer, Herbert (1986). What is wrong with social theory? In Herbert Blumer, Symbolic interactionism: Perspective and method (pp ). Berkeley: University of California Press. Gilgun, Jane F. (2005). Qualitative research and family psychology. Journal of Family Psychology,19(1), Gilgun, Jane F. (2002). Conjectures and refutations: Governmental funding and qualitative research. Qualitative Social Work, 1(3), Gilgun, Jane F. (2001). "Case Study Research, Analytic Induction, and Theory Development: The Future and the Past," ( November) paper presented at the Preconference Workshop on Theory Development and Research Methodology, National Conference on Family Relations, Rochester, NY, November Gilgun, Jane F. (1999). Fingernails painted red: A feminist, semiotic analysis of "hot" text, Qualitative Inquiry, 5, Gilgun, Jane F., & Laura McLeod (1999). Gendering violence. Studies in Symbolic Interactionism, 22, Glaser, Barney (1978). Theoretical sensitivity. Mill Valley, CA: Sociology Press. Glaser, Barney (1992). Basics of grounded theory analysis. Mill Valley, CA: Sociology Press. Glaser, Barney & Anselm Strauss (l967). The discovery of grounded theory. Chicago: Aldine. Patton, Michael Quinn (2002). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks, CA: Sage Popper, Karl R. (1969). Conjectures and refutations: The growth of scientific knowledge. London: Routledge and Kegan Paul. Strauss, Anselm (l987). Qualitative analysis for social scientists. New York: Cambridge University Press. Strauss, Anselm & Juliet Corbin (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd ed.). Thousand Oaks, CA: Sage. Van Maanen, John (1988). Tales of the field: On writing ethnography. Chicago: University of Chicago Press. Van Manen, Max (1990). Researching lived experience: Human science for an action sensitive pedagogy. Albany: State University of New York.

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