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E-grāmata: Single-case and Small-n Experimental Designs: A Practical Guide To Randomization Tests, Second Edition

2.75/5 (7 ratings by Goodreads)
(Dundee University, UK), , (University of Abertay, Dundee, UK)
  • Formāts: 304 pages
  • Izdošanas datums: 27-Apr-2012
  • Izdevniecība: Routledge
  • Valoda: eng
  • ISBN-13: 9781136588471
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Single-case and Small-n Experimental Designs: A Practical Guide To Randomization Tests, Second EditionPalielināt
  • Formāts: 304 pages
  • Izdošanas datums: 27-Apr-2012
  • Izdevniecība: Routledge
  • Valoda: eng
  • ISBN-13: 9781136588471
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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 books website so that users can run analyses of the text data as well as data from their own studies.

The new edition features:





More explanation as to why randomization tests are useful and how to apply them. More varied and expanded examples that demonstrate the use of these tests in education, clinical work and psychology. A website with the macros and datasets for all of the text examples in IBM SPSS and Excel. Exercises at the end of most chapters that help readers test their understanding of the material. A new glossary that defines the key words that appear in italics when they are first introduced. A new appendix that reviews the basic skills needed to do randomization tests. New appendices that provide annotated SPSS and Excel macros to help readers write their own or tinker with the ones provided in the book.

The book opens with an overview of single case and small n designs -- why they are needed and how they differ from descriptive case studies. Chapter 2 focuses on the basic concepts of randoization tests. Next how to choose and implement a randomization design is reviewed including material on how to perform the randomizations, how to select the number of observations, and how to record the data. Chapter 5 focuses on how to analyze the data including how to use the macros and understand the results. Chapter 6 shows how randomization tests fit into the body of statistical inference. Chapter 7 discusses size and power. The book concludes with a demonstration of how to edit or modify the macros or use parts of them to write your own.

Ideal as a text for courses on single-case, small n design, and/or randomization tests taught at the graduate level in psychology (especially clinical, counseling, educational, and school), education, human development, nursing, and other social and health sciences, 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 books accessible approach. An introduction to basic statistics, SPSS, and Excel is assumed.

Recenzijas

"The presentation is good, and the authors give a practical resource for those who must work with the specific designs in the text." Technometrics "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 individuals 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

"Im very excited about this book. ... The authors bring up the issues that Ive found [ students] to struggle with. ... This text will align well with NIHs and NIMHs 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

Preface ix
Chapter 1 Single-case and small-n designs in context
1(10)
Intrduction
1(3)
Single-case and small-n designs in the research process
4(3)
Randomization tests' time has come
7(1)
Using this book
7(4)
Chapter 2 Understanding randomization tests
11(26)
An introductory example: testing for extrasensory perception (ESP)
11(3)
Classes of randomization tests
14(2)
Hypothesis tests for randomization designs
16(15)
How randomization tests differ from more familiar tests
31(1)
Why randomization tests are not widely used
32(1)
Two ways to obtain the reference set
33(1)
The number of arrangements needed for significance to be achievable
34(1)
Exercises
35(2)
Chapter 3 Obtaining the data: Choosing the design
37(16)
Introduction
37(4)
Designs analogous to ANOVA
41(4)
Phase designs
45(5)
A design to investigate order effects
50(1)
Exercises
51(2)
Chapter 4 Obtaining the data: Implementing the design
53(40)
Introduction
53(1)
Designs analogous to ANOVA
54(24)
Phase designs
78(12)
A design to test order effects
90(2)
Exercises
92(1)
Chapter 5 Analyzing the data: Using the macros
93(38)
Introduction
93(1)
Analyses using the SPSS macros
94(16)
Analyses using the Excel macros
110(20)
Exercises
130(1)
Chapter 6 Analyzing the data: Wider considerations
131(16)
Introduction: the myth of the random sample
131(1)
Randomization
132(4)
Phase designs: response guided intervention
136(6)
Incomplete randomization
142(2)
Exercises
144(3)
Chapter 7 Size and power
147(12)
Introduction
147(1)
Estimating a by sampling the reference set
147(1)
Size and power: some terminology
148(2)
Maximizing power
150(4)
Power of randomization tests
154(3)
Exercises
157(2)
Chapter 8 Going further
159(14)
Introduction
159(1)
Other sources of software for randomization tests
159(3)
Writing your own macros: some general advice
162(1)
Using parts of our macros to write one of your own: an example
163(7)
Further reading
170(3)
Solutions to even numbered exercises 173(4)
Appendix 1 177(10)
Appendix 2 187(42)
Appendix 3 229(46)
Glossary 275(6)
References 281(2)
Author Index 283(2)
Subject Index 285
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.
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