Qualitative Analysis: Eight Approaches for the Social Sciences
By Margaretha Jarvinen and Nanna Mik-Meyer
Published February 2020 by SAGE Publications Ltd. ($106 hardback; $36 paperback; e-books also available)
This introductory, researcher- and student-friendly textopens in new window surveys a variety of approaches to qualitative analysis. Particular emphasis is paid to translating theory into practice. The book provides a detailed explanation of each of the eight approaches, with two chapters dedicated to each approach: one chapter to describe the theory and one chapter to outline the practical applications. Topics include narrative analysis, network theory, and interviewing techniques, among other models and theories. The entire research process is outlined, from theory generation to data collection to data analysis and reporting.
Analyzing Group Interactions: A Guidebook for Qualitative, Quantitative, and Mixed Methods
By Matthias Huber and Dominik E. Froehlich
Published May 2020 by Routledge ($155 hardback; $47.95 paperback)
The book offers a systematic approach to understand a variety of methods to explore group interactions in social science research contexts. Subject-matter experts from various fields provide pragmatic step-by-step advice about handling group interaction analyses, including approaches that are qualitative, quantitative or a combination of the two methods. Topics include ethnography, phenomenology, content analysis, discourse analysis, social network analysis and survey or questionnaire ratings. Researchers of all levels may find this text useful in their work, as it can help guide research design, planning and analysis.
Data Science and Machine Learning: Mathematical and Statistical Methods
By Dirk P. Kroese, Zdravko Botev, Thomas Taimre, Radislav Vaisman
Published November 2019 by Chapman and Hall/CRC Press ($99.95 hardback; e-books also available)
In this book, students and researchers alike will be introduced to key concepts related to machine-learning algorithms. The text is accessible to most audiences, written to provide deeper understanding and without the expectation of prior expertise in data science. Exercises, examples and programming code snippets are provided throughout for concrete applications and practice. It covers mathematical theorems to provide background and foundations, and it extends the basics to cover more sophisticated topics such as complex prediction algorithms, classification models and decision trees. Additional chapters include discussions and examples regarding data structure, visualization and cross-validation.
Rasch Measurement: Applications in Quantitative Educational Research
By Myint Swe Khine
Published January 2020 by Springer ($139.99 hardback; e-books also available)
Educational measurement scholars and researchers may find this book to be a useful guide for analyzing psychometric properties of test instruments. The history and theory of Rasch models are discussed, along with practical applications and recent innovations. The latest approaches and best practices are detailed and demonstrated through realistic examples. Each chapter in this edited book is written by a notable researcher in the field, in which they describe the theory and applications of topics such as questionnaires, classroom settings and familiarization of novice users.
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