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Zusatztext "This new edition provides an excellent treatment of both the design and the analysis of single-case and small-n designs. It emphasizes the importance of matching the design to the analysis! and uses the many strengths of randomization tests to overcome problems with standard parametric procedures applied to small-sample studies." - David C. Howell! University of Vermont! USA"This book provides statistical methods appropriate for small n studies--studies that may be messy! exploratory! and fail many of the assumptions of classical methods. A must-read for researchers conducting field research in educational and training environments." - Gregory K.W.K. Chung! UCLA/CRESST! USA"Although we have known for many years that single case experimental designs are essential for the evaluation of an individual's response to treatment! most of us do not employ randomization strategies when planning this treatment. We need to change and this book will enable us to do just that. I urge all clinical and neuro psychologists interested in treating patients to purchase this book." - Barbara A Wilson! Oliver Zangwill Centre! Ely! UK"I'm very excited about this book. ... The authors ? bring up the issues that I've found [students] to struggle with. ... This text will align well with NIH's and NIMH's move towards translational research and focus on evidenced-based treatment validity. ...The authors have an incredibly clear! thoughtful writing style. ... This text will "bridge the gap" between required course content and the reality that students will face in the field. ... I plan to buy it! use it in my class! and tell everyone I can about it." - Marie S. Hammond! Tennessee State University! USA"The text ... fills a gap in the scholarly literature desperately needed in the behavior analytic scientific community. ... [There] are no directly competing texts that go into such depth ? for single-subject research designs as they are used specifically within clinical psychology and behavior analysis. ... [It is] an invaluable ? reference." - Michele Ennis Soreth! Rowan University! USA Informationen zum Autor Pat Dugard taught statistics at the University of Abertay Dundee until 1999 and has also taught courses at the Open University. She now concentrates on writing. She received her PGDip in Mathematical Statistics from the University of Cambridge. Portia File is a psychologist and computer scientist experienced in teaching university courses on research methods. She taught at University of Abertay Dundee from 1983 until 2007. She received her PhD in Cognitive Psychology from the University of Texas at Austin in 1975. Jonathan Todman is a Clinical Psychologist in the Pain Management Programme at NHS Greater Glasgow and Clyde in Glasgow, Scotland. He received his Clinical Psychology Doctorate from Edinburgh in 2010. Klappentext This practical guide explains the use of randomization tests and provides example designs and macros for implementation in IBM SPSS and Excel. It reviews the theory and practice of single-case and small-n designs so readers can draw valid causal inferences from small-scale clinical studies. The macros and example data are provided on the book's website so that users can run analyses of the text data as well as data from their own studies.Ideal as a text for graduate-level courses on single-case, small-n design, and/or randomization tests, this inexpensive book also serves as a supplement in statistics or research methods courses. Practitioners and researchers with an applied clinical focus also appreciate this book's accessible approach. Zusammenfassung This practical guide explains the use of randomization tests and provides example designs and macros for implementation in IBM SPSS and Excel. It reviews the theory and practice of single-case and small- n designs so readers can draw valid causal inferences from small-scale clini...
