Dedoose Publications

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

Integrating Quantitative and Qualitative Research: How is it Done?

Bryman, Alan (2006)

Qualitative Research, 6(1), 97-113

This article seeks to move beyond typologies of the ways in which quantitative and qualitative research are integrated to an examination of the ways that they are combined in practice. Draws on a content analysis of methods and design from 232 articles using combined methods. Examine and discusses the rationales provide for employing mixed-methods and whether they correspond to actual practice.
Education Based Publications

Qualitative and Quantitative Methods

Bernard, H. Russell & Ryan, Gery W. (1998)

Handbook of Methods in Cultural Anthropology, pp. 595-646. Walnut Creek, CA: Altamira Press

Complete presentation and discussion of steps and strategies for analyzing text from a variety of qualitative research orientations
Education Based Publications

Distinguishing the Trees from the Forest: Applying Cluster Analysis to Thematic Qualitative Data

Guest, Greg & McLellan, Eleanor (2003)

Field Methods, 15(2): 186-201

Qualitative data analysis requires organizing and synthesizing often large quantities of text. In many cases, this analysis entails negotiating the interplay between raw data, semantic themes or codes, and the overarching conceptual framework. In this article, the authors use a case study, which examines HIV vaccine efficacy trial participants' discourse, to demonstrate how cluster analysis can be used to aid in the analysis of large qualitative data sets. After briefly reviewing the systematic approaches to qualitative analysis and describing the project background, the authors present an example of how a hierarchical cluster technique can be incorporated into a multistage thematic analysis. Cited by Macia In this article I discuss cluster analysis as an exploratory tool to support the identification of associations within qualitative data. While not appropriate for all qualitative projects, cluster analysis can be particularly helpful in identifying patterns where numerous cases are studied. I use as illustration a research project on Latino grievances to offer a detailed explanation of the main steps in cluster analysis, providing specific considerations for its use with qualitative data. I specifically describe the issues of data transformation, the choice of clustering methods and similarity measures, the identification of a cluster solution, and the interpretation of the data in a qualitative context. Keywords: Cluster Analysis, Qualitative Analysis, Data Exploration, Mixed
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

Systematic Field Observation

McCall, George J. (1984)

Annual Review of Sociology, 10: 263-282

Discusses the history and types of field observation methods from a sociological perspective. Offers a role-expectations view of observation systems requiring a reconceptualization of system development and the nature, sources, and management of error.
Medical Based Publications

"I speak a different dialect": Teen Explanatory Models of Difference and Disability

Daley, Tamara, & Weisner, Thomas S. (2003)

Medical Anthropology Quarterly, 17(1): 25-48

fter eras of “blaming” parents for their children’s disabilities and relying on biomedical labels as both correct and sufficient to explain and name various conditions, research and practice today recognize the significance of the meaning and understanding of disabilities held by family members and children themselves. What do teens with disabilities believe about their circumstances, and what do they understand to be the causes, correlates, and consequences of their conditions? Elicited explanatory models from adolescents with varied cognitive disabilities and delay to better understand their personal experiences
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.
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.
Geography Based Publications

Evaluating Qualitative Research in Social Geography: Establishing ‘Rigour’ in Interview Analysis

Baxter, Jamie; Eyles, John (1997)

A review of 31 empirical and 18 substantive papers by qualitative social geographers mainly using in-depth interviews reveals little explicit reference to the principle(s) adopted to enhance ‘rigour’ and to ensure meaningful inference. Given the modest explicit discussion of evaluative criteria in these papers, a scheme from evaluation research itself is critically reviewed. A set of evaluation questions derived from this review and their application to an empirical piece of qualitative work frame an argument for a general set of criteria rather than rigid rules for assessing qualitative work. Such criteria can serve as anchor points for qualitative evaluation.
Medical Based Publications

Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples

David Henry, Allison B. Dymnicki, Nathaniel Mohatt, James Allen, James G. Kelly (2015)

Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.
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