Dedoose Publications

Dedoose has been field-tested and journal-proven by leading academic institutions and market researchers worldwide. Thousands of prominent researchers across the US and abroad have benefited from early versions of Dedoose in their qualitative and mixed methods work and have laid an outstanding publication and report trail along the way.

Education Based Publications

Barriers to Integrating Quantitative and Qualitative Research

Bryman, A. (2007)

Journal of Mixed Methods Research, 1(1): 8-22

This article is concerned with the possibility that the development of mixed methods research is being hindered by the tendency that has been observed by some researchers for quantitative and qualitative findings either not to be integrated or to be integrated to only a limited extent. It examines findings from 20 interviews with U.K. social researchers, all of whom are practitioners of mixed methods research. From these interviews, a wide variety of possible barriers to integrating mixed methods findings are presented. Challenges to integrating mixed methods data and strategy for writing mixed methods research articles.
Sociology Based Publications

The Mixed Methods Reader

Plano Clark, V. L., & Creswell, J. W. (2008)

Los Angeles: Sage

In recent years, researchers have begun to combine quantitative and qualitative approaches within single study research designs. As such, the literature on mixed methods research has grown at a rapid pace. While more methodological books addressing mixed methods are becoming available, the foundational writings of this field are still scattered across diverse disciplines and their wide range of publications outlets, leaving students and researchers at a disadvantage to find the exemplary or model studies to help them understand how to conduct their own mixed methods research. In light of the dispersed nature of the mixed methods literature, The Mixed Methods Reader editors have organized a collection of key methodological mixed methods discussions and exemplar mixed methods research studies in one easy-to-access location. This integrative collection draws from the international literature appearing across diverse research disciplines over the past thirty years. The Mixed Methods Reader is divided into two parts: Part I – Methodological Selections and Part II – Exemplar Research Studies. Part I includes a collection of 14 foundational writings from the mixed methods research literature. These readings convey the overall development and evolution of mixed methods research and address essential topics for researchers new to the field of mixed methods research. These topics include its foundations; design types; implementation issues such as sampling, data analysis, and validity; rhetorical devices for reporting mixed methods studies; and critiques about the current thinking in the field. Part II includes 9 exemplar mixed methods research studies drawn from a range of disciplines and international scholars. The studies were intentionally selected to illustrate four major types of mixed methods designs. As with the methodological chapters, the editors organize the exemplar research studies so that the reader can see a natural progression of the different approaches to conducting mixed methods research. The Mixed Methods Reader, edited by two leading researchers in mixed methods research, offers students and researchers a rich balance of foundational works and exemplary studies across a range of disciplines. This reader is an invaluable primary or supplementary resource for courses that address mixed methods research. Key Features: Each of the 14 foundational readings offers a brief introduction by the editors, discussing the reading's overall importance to mixed methods research and explaining what aspect of the research process is addressed. The foundational readings are organized around the research process to facilitate its use as a text or supplement for research courses emphasizing mixed methods approaches. They cover research design types and purposes, data collection, data analysis, reporting of mixed methods studies, and future directions. Each of the 9 exemplary studies include a brief commentary from the editors, highlighting the noteworthy features of the article. These exemplary studies range in discipline and setting yet focus intently on the research process and the various ways of conducting mixed methods studies. Visual diagrams accompany each exemplary study: These visual diagrams will convey the overall structure and approach used in each of the studies. Discussion questions accompanying each selection further call attention to the key points and help a student or individual researcher to tie together the core concepts presented in the commentaries and articles.
Education Based Publications

Intercoder Reliability for Validating Conclusions Drawn from Open-Ended Interview Data

Kurasaki, Karen S. (2000)

Field Methods, 12(3): 179-194

Intercoder reliability is a measure of agreement among multiple coders for how they apply codes to text data. Intercoder reliability can be used as a proxy for the validity of constructs that emerge from the data. Popular methods for establishing intercoder reliability involve presenting predetermined text segments to coders. Using this approach, researchers run the risk of altering meanings by lifting text from its original context, or making interpretations about the length of codable text. This article describes a set of procedures that was used to develop and assess intercoder reliability with free-flowing text data, in which the coders themselves determined the length of codable text segments. Discusses procedures for developing and assessing intercoder reliability with free-flowing text.
Education Based Publications

Research Design Issues for Mixed Method and Mixed Model Studies

Tashakkori, Abbas & Teddlie, Charles (1998)

A. Tashakkori & C. Teddlie, Mixed Methodology: Combining Qualitative and Quantitative Approaches, pp. 40-58

Discusses the concept of triangulation from various perspectives and the variety of approaches to implementing mixed methods research. Builds on Patton’s (1990) discussion of ‘mixed form’ design to a broader model in order to develop a taxonomy for distinguishing various mixed method designs and approaches.
Education Based Publications

Mixing Qualitative and Quantitative Methods: Insights into Design and Analysis Issues

Lieber, Eli (2009)

Journal of Ethnographic and Qualitative Research, 3: 218-227

Discusses issues of design, sampling, and analysis in mixed methods research. Offers a model for conceptualizing a fully integrated design. Proposes and illustrates strategies for managing and dynamically integrating the qual and quant data to allow for efficient and multi-directional analysis. It is increasingly desirable to use multiple methods in research, but questions arise as to how best to design and analyze the data generated by mixed methods projects.
Education Based Publications

Developing Data Analysis

Silverman, David (2005)

Doing Qualitative Research, 2nd Edition (pp. 171-187)

Provides a step-by-step guide to all the questions students ask when beginning their first research project. Silverman demonstrates how to learn the craft of qualitative research by applying knowledge about different methods to actual data. He provides practical advice on key issues such as defining ‘originality’ and narrowing down a topic, keeping a research diary and writing a research report, and presenting research to different audiences.
Education Based Publications

Lessons Learned for Teaching Mixed Research: A Framework for Novice Researchers

Onwuegbuzie, Anthony J. & Leech, Nancy L. (2009)

International Journal of Multiple Research Approaches, 3(1), 105-107

A concise description of key steps in the mixed research process. The authors further map this process onto issues/controversies in the use of mixed methods research and the challenges mixed methods researchers face.
Education Based Publications

Toward a Unified Validation Framework in Mixed Methods Research

Dellinger, Amy B. & Leech, Nancy L. (2007)

Journal of Mixed Methods Research, 1(4), 309-332

Offers a validation framework to guide thinking about validation in mixed methods work. An orientation from both qualitative and quantitative perspectives is used to set the foundation for discussing and thinking about validation issues. To justify the use of this framework, the authors discuss traditional terminology and vailidity criteria for quantitative and qualitative research, as well as present recently recently published validity terminology for mixed methods research.
Sociology Based Publications

Qualitative Data Analysis

Seidel, John V. (1998)

Qualis Research

This is an essay on the basic processes in qualitative and mixed methods data analysis (QDA). It serves two purposes. It is a simple introduction for the newcomer of QDA. QDA is a process of noticing, collecting and thinking about interesting things. The purpose of this model is to show that there is asimple foundation to the complex and rigorous practice of QDA. Once you grasp this foundation you can move in many different directions. The idea for this model came from a conversation with one of my former teachers, Professor Ray Cuzzort. Ray was teaching an undergraduate statistics course and wanted to boil down the complexity of statistics to a simple model. His solution was to tell the students that statistics was a symphony based on two notes: means and standard deviations. I liked the simplicity and elegance of his formulation and decided to try and come up with a similar idea for describing QDA. The result was the idea that QDA is a symphony based on three notes: Noticing, Collecting, and Thinkingabout interesting things. While there is great diversity in the practice of QDA I would argue that all forms of QDA are based on these three “notes.” The QDA process is not linear. When you do QDA you do not simply Notice, Collect, and then Think about things, and then write a report. Rather, the process has the following characteristics: -Iterative and Progressive: The process is iterative and progressive because it is a cycle that keeps repeating. For example, when you are thinking about things you also start noticing new things in the data. You then collect and think about these new things. In principle the process is an infinite spiral. -Recursive: The process is recursive because one part can call you back to a previous part. For example, while you are busy collecting things you might simultaneously start noticing new things to collect. -Holographic: The process is holographic in that each step in the process contains the entire process. For example, when you first notice things you are already mentally collecting and thinking about those things. Thus, while there is a simple foundation to QDA, the process of doing qualitative data analysis is complex. The key is to root yourself in this foundation and the rest will flow from this foundation.
Education Based Publications

Managing Data in CAQDAS

Fielding, Nigel & Lee, Ray M. (1998)

Chapter 4 in Fielding & Lee, Computer Analysis and Qualitative Research, pp. 86-118

from COMPUTER ASSISTED QUALITATIVE DATA ANALYSIS SOFTWARE: A PRACTICAL PERSPECTIVE FOR APPLIED RESEARCH, JOSEPH B. BAUGH, ANNE SABER HALLCOM, and MARILYN E. HARRIS Computer assisted qualitative data analysis software (CAQDAS) holds a chequered reputation to date in academia, but can be useful to develop performance metrics in the field of corporate social and environmental responsibility and other areas of contemporary business. Proponents of using CAQDAS cite its ability to save time and effort in data management by extending the ability of the researcher to organize, track and manage data. Opponents decry the lack of rigor and robustness in the resultant analyses. Research reveals that these opinions tend to be divided by “the personal biography and the philosophical stance of the analyst” (Catterall & Maclaran, 1998, p. 207), as well as “age, computer literacy, and experience as a qualitative researcher” (Mangabeira, Lee & Fielding, 2004, p. 170). A more recent article (Atherton & Elsmore 2007) discussed the continuing debate on CAQDAS in qualitative research: The two perspectives both indicate that CAQDAS should be used with care and consideration; in ways that explicitly demonstrate a “fit” between the ethos and philosophical perspective(s) underpinning a research study, on the one hand, and the means of ordering and manipulating the data within CAQDAS on the other. (p. 75) Despite the ongoing literary debate on the merits of CAQDAS, the use of computer-aided qualitative data analysis has become acceptable to most qualitative researchers (Lee & Esterhuizen; Morison & Moir, 1998; Robson, 2002). However, writers advise that researchers avoid the trap of letting the software control the data analysis (Catterall & Maclaran, 1998). Morison and Moir counseled that CAQDAS is merely one tool in the qualitative data analysis toolbox. No tool should replace the researcher's capacity to think through the data and develop his or her emergent conclusions (Atherton & Elsmore, 2007). On the other hand, Morison and Moir among others (e.g., Blank, 2004; Catterall & Maclaran, 1998; Mangabeira et al., 2004) found the use of qualitative data analysis software can also free up significant amounts of time formerly used in data management and encoding allowing the researcher to spend more time in deeper and richer data evaluation. Qualitative research studies to develop performance metrics can create huge amounts of raw data (Miles & Huberman, 1994; Robson, 2002). Organizing, tracking, encoding, and managing the data are not trivial tasks and the effort should not be underestimated by the applied researcher. Two methodologies exist to handle these activities and manage the data during the data analysis phase. The first methodology is a manual process, which must be done at times to avoid missing critical evidence and provide trustworthiness in the process (Malterud, 2001), while the second methodology indicates the use of technology for managing the data and avoid being overwhelmed by the sheer amount of raw data (Lee & Esterhuizen, 2000). It is the experience of the authors that some manual processing must be interspersed with CAQDAS. This provides an intimacy with the data which leads to the drawing of credible and defensible conclusions. Thus, a mixed approach that melds manual and automated data analyses seems most appropriate. A basic approach for applying traditional qualitative research methodologies lies in the ability of CAQDAS to support data reduction through the use of a “provisional start list” (Miles & Huberman, 1994, p. 58) of data codes that are often developed manually from the research question. A rise in the use of CAQDAS for applied research and other nonacademic research fields has been identified (Fielding & Lee, 2002). Since CAQDAS is becoming more prevalent in nonacademic researcher populations and can be useful for developing performance metrics for corporate social and environmental responsibility and solving other complex business issues, it seems prudent at this juncture to discuss how to use the software appropriately rather than rehash the argument for or against using CAQDAS. Selection of and training with an appropriate CAQDAS package can help the researcher manage the mountains of data derived from qualitative research data collection methods (Lee & Esterhuizen, 2000).
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