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A01=Dan James Kaczynski
A01=Dan Kaczynski
A01=Eli Lieber
A01=Michelle Salmona
A01=Michelle Suzanne Salmona
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Author_Dan James Kaczynski
Author_Dan Kaczynski
Author_Eli Lieber
Author_Michelle Salmona
Author_Michelle Suzanne Salmona
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Category=JHBC
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COP=United States
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Qualitative and Mixed Methods Data Analysis Using Dedoose: A Practical Approach for Research Across the Social Sciences

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Qualitative and Mixed Methods Data Analysis Using Dedoose®: A Practical Approach for Research Across the Social Sciences provides both new and experienced researchers with a guided introduction to dealing with the methodological complexity of mixed methods and qualitative inquiry using Dedoose® software. The authors use their depth of experience designing and updating Dedoose® as well as their published research to give the reader practical strategies for using Dedoose® from a wide range of research studies. Case study contributions by outside researchers provide readers with rich examples of how to use Dedoose® in practical, applied social science and health settings.  See more
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A01=Dan James KaczynskiA01=Dan KaczynskiA01=Eli LieberA01=Michelle SalmonaA01=Michelle Suzanne SalmonaAge Group_UncategorizedAuthor_Dan James KaczynskiAuthor_Dan KaczynskiAuthor_Eli LieberAuthor_Michelle SalmonaAuthor_Michelle Suzanne Salmonaautomatic-updateCategory1=Non-FictionCategory=GPSCategory=JHBCCategory=UFCategory=UNCCOP=United StatesDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=AvailablePrice_€50 to €100PS=Activesoftlaunch
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Product Details
  • Weight: 470g
  • Dimensions: 187 x 231mm
  • Publication Date: 07 Nov 2019
  • Publisher: SAGE Publications Inc
  • Publication City/Country: United States
  • Language: English
  • ISBN13: 9781506397818

About Dan James KaczynskiDan KaczynskiEli LieberMichelle SalmonaMichelle Suzanne Salmona

Dr. Michelle Salmona serves as President (co-founder) of the Institute for Mixed Methods Research (IMMR) with an academic appointment as Adjunct Professor at the University of Canberra Australia. She has authored multiple books and academic papers including her book co-authored with Dan Kaczynski and Eli Lieber Qualitative and Mixed Methods Data Analysis Using Dedoose: A Practical Approach for Research Across the Social Sciences. Michelle has been working for over 20 years as a mentor in writing about strong research and a teacher in qualitative data analysis and the use of Qualitative Data Analysis Software (QDAS). In addition she is a credentialed project management professional (PMP) and senior fellow of the Higher Education Academy United Kingdom. Michelle is a specialist in qualitative and mixed methods research design and analysis and works as an international consultant in: program evaluation; research design; and mixed-methods and qualitative data analysis using digital tools. Her research focus is to better understand how to support doctoral success and strengthen the research process; and build data-driven decision-making capacity through technological innovation. Recent research includes exploring the changing practices of qualitative research during the dissertation phase of doctoral studies and investigating how we bring learning into the use of technology during the research process. Michelle is currently working on projects with researchers from education information systems business communication leadership and finance. Dr. Eli Lieber is an interdisciplinary social scientist methodologist and data analyst.  He has spent over 20 years at the University of California Los Angeles focused on advancing our thinking about and strategically implementing qualitative and mixed methods approaches in social science research.  Initially trained as a quantitative psychologist he soon began working with colleagues from other social science disciplines and came to appreciate the deep importance and role in qualitative perspectives.  From a practical view he believes that the informed integration of methods study design and the data generated produce more comprehensive and robust research findings than those from more method-centric approaches. Dr. Liebers recent work has focused on the continued development of mixed methods strategies and technologies.  Eli is particularly interested in what we do with all the data we gather: How can data be integrated and what evolving technologies can make our research and evaluation work and findings more efficient effective and sustainable? Eli looks forward to his work with Institute for Mixed Methods Research (IMMR) colleaguesa truly global and diverse group of individuals.  The IMMR mission will be an ongoing service to building methodological capacity relationship building engagement and communication regarding evolving mixed methods work and bringing the deep experience of IMMR associates into the service of others employing these practices.  Dr. Lieber is optimistic about how mixed methods research and IMMR can advance social science through engaging with colleagues directly through connections within larger institutions organizations and through the forging of strategic partnerships. Professor Dan Kaczynski is Professor Emeritus at Central Michigan University and a senior research fellow at the IMMR. He is currently an adjunct professor supervising doctoral candidates at the University of Canberra Australia. His research interests promote technological innovations in qualitative and mixed meth­ods data analysis in the social sciences in the United States and Australia. Dan is a program evaluation consultant and has more than 20 years experience conducting state national and international evaluations. Leadership roles include K-12 and higher education administration and research center director with extensive experience as principal investigator of more than $35 million in grant awards. His work has been shared professionally with more than 250 professional presentations nationally and internationally. He has written more than 50 published research articles and eight books and book chapters. In addition he has supervised over 100 doctoral dissertations and professional specialist theses. 

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