Single-Case and Small-N Experimental Designs: A Practical Guide to Randomization Tests

✍ Scribed by Pat Dugard; Portia File; Jonathan Todman

• Publisher: Routledge
• Year: 2011
• Tongue: English
• Leaves: 305
• Edition: 2
• Category: Library

✦ Synopsis

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.

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 book's accessible approach. An introduction to basic statistics, SPSS, and Excel is assumed.

✦ Table of Contents

Cover
Single-case and Small-n Experimental Designs: A Practical Guide to Randomization Tests
Copyright
Contents
Preface
chapter one Single-case and small-n designs in context
Introduction
Single-case and small-n designs in the research process
Randomization tests’ time has come
Using this book
chapter two Understanding randomization tests
An introductory example: testing for extrasensory perception (ESP)
Classes of randomization tests
Hypothesis tests for randomization designs
How randomization tests differ from more familiar tests
Why randomization tests are not widely used
Two ways to obtain the reference set
The number of arrangements needed for significance to be achievable
Exercises
chapter three Obtaining the data: Choosing the design
Introduction
Designs analogous to ANOVA
Phase designs
A design to investigate order effects
Exercises
chapter four Obtaining the data: Implementing the design
Introduction
Designs analogous to ANOVA
Phase designs
A design to test order effects
Exercises
chapter five Analyzing the data: Using the macros
Introduction
Analyses using the SPSS macros
Analyses using the Excel macros
Exercises
chapter six Analyzing the data: Wider considerations
Introduction: the myth of the random sample
Randomization
Phase designs: response guided intervention
Incomplete randomization
Exercises
chapter seven Size and power
Introduction
Estimating α by sampling the reference set
Size and power: some terminology
Maximizing power
Power of randomization tests
Exercises
chapter eight Going further
Introduction
Other sources of software for randomization tests
Writing your own macros: some general advice
Using parts of our macros to write one of your own: an example
Further reading
Solutions to even numbered exercises
Appendix 1: Basic skills for randomization tests
Appendix 2: SPSS macros
Appendix 3: Excel macros
Glossary
References
Author Index
Subject Index