
- 336 pages
- English
- PDF
- Available on iOS & Android
About this book
Single Subject Research: Strategies for Evaluating Change presents an overview of strategies used to evaluate change in single subject research, a particular approach referring to time-series paradigms in which each subject is used repeatedly. These strategies include research design, graphical analysis, and statistical tests, and it will be apparent that such designs extend beyond those commonly employed in applied behavioral research. The book opens with a brief historical perspective of time-series and other small group research. Separate chapters follow covering the analysis of graphic data as being of singular importance in single subject research; the units-of-analysis issue and a nonparametric randomization approach to data analysis; and the growing awareness among researchers that understanding the individual characteristics of interacting subjects may be inadequate for understanding the process that has taken place between them. The final chapter reviews the advantages and disadvantages of the analytic methods presented in the previous chapters. This volume will be of interest to those individuals actively engaged in educational and psychological experimentation for which single subject research strategies are or may prove to be valuable. Students desiring to supplement their knowledge of a unique and rapidly emerging area of statistical analysis as applied to single subject research designs will also find this volume of importance.
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Information
Table of contents
- Front Cover
- Single Subject Research: Strategies for Evaluating Change
- Copyright Page
- Table of Contents
- List of Contributors
- Foreword
- Preface
- Chapter 1. Foundations of Time-Series Research
- Chapter 2. The Analysis and Presentation of Graphic Data
- Chapter 3. N = Nonparametric Randomization Tests
- Chapter 4. Analysis of Interrupted Time-Series Experiments
- Chapter 5. Sequential Analysis of Observational Data Using Markov Chains
- Chapter 6. Choosing a Statistical Method for Analysis of an Intensive Experiment
- Index