Scientific methods are the ‘how to’ aspects of a research project including who or what setting to be studied, which data to collect, how to collect
these data, how to manage and integrate these data, and how to approach the data analysis. Qualitative methods are, by nature, relatively open-ended and
include interviews, stories, observations, and notes. These data are typically approached through substantive content analysis, explored for a priori
and emergent themes, excerpted and coded, and explored for the deeper patterns within commonly coded excerpts and the relations between differentially
coded content. Quantitative methods include the use of measurement scales, checklists, tests, demographics, and the application of code weight systems
and are typically analyzed through univariate, bivariate, and multivariate statistical techniques. Mixed method research is the flexible and creative
application of some variety of approaches within a research project. In these studies, methodological decisions are problem-based, rather than method
based, to allow researchers to benefit from the strengths inherent in both qualitative and quantitative approaches. This blending can take many forms
and, accordingly, the approaches can be responsive and adaptive.
Qualitative data are valued for being rich, natural, detailed, contextualized, sensitive, and filled with the authentic and complex representations
through which people communicate meaning in their lives. Quantitative data are highly structured, relatively inexpensive to collect and analyze, and
central to the systematic study of empirical (numbers) properties and relationships. Quantitative data tell us a great deal about things like how many
people are like ‘this or that’, which characteristics of the world are related to each other, and how many people benefited from a new program or intervention.
Qualitative data tell us more about ‘how’ and ‘why’ things are happing in people’s day-to-day activities and routines, the nature of the relations between
phenomena in the world, and the mechanisms through which people may have benefited from a new program or intervention. Naturally, getting the best of both
from both approaches broadens and deepens our understanding of the phenomena on which we focus our research.
Dedoose was designed and built for one primary purpose—to facilitate the management and analysis of the data that come from mixed methods research.
There are great tools for analyzing quantitative data and great tools for analyzing qualitative data, but Dedoose is breaking new ground in serving the
growing number of researchers and research teams using qualitative and mixed methods by making it fast, easy, collaborative, effective, and inexpensive
to carry out the data management, analysis, and presentation tasks that are fundamental to qualitative and mixed methods research.