Design and Analysis of Single-Case Research

This book focuses on one important aspect of psychological research -- the intensive study of people measured one or more at a time. Some important historical material is detailed in several chapters making a strong connection to previous material in psychology. Several contributors present important details on classical and novel methods to study behavior over time, and they do so in the context of appropriate statistical methods. This appropriately reflects the growing interest in examining dynamic behaviors by objective measurement. Key experimental design principles are expertly stated, reflecting the growing interest in studying the individual course of development for invariants in behaviors, including some unusual constructs such as cycles and punctuated equilibria. This book also deals with practical contemporary problems in psychology and documents the increased possibility of using clinical research tools. Taken as a whole, this volume is filled with interesting historical points, informative mathematical and statistical analyses, and practical methods. It is the only book addressing the issues of meta-analysis, cyclicity, and confounds to visual inspection of single subject data that considers ways in which statistical software can aid in overcoming these constraints.

Contents: Preface. R.D. Franklin, D.B. Allison, B.S. Gorman, Introduction. R.F. Ittenbach, W.F. Lawhead, Historical and Philosophical Foundations of Single-Case Research. L.H. Primavera, D.B. Allison, V.C. Alfonso, Measurement of Dependent Variables. F.M. Gresham, Treatment Integrity in Single-Subject Research. R.D. Franklin, B.S. Gorman, T.M. Beasley, D.B. Allison, Graphical Display and Visual Analysis. B.S. Gorman, D.B. Allison, Statistical Alternatives for Single-Case Designs. T.A. Matyas, K.M. Greenwood, Serial Dependency in Single-Case Time Series. M.S. Faith, D.B. Allison, B.S. Gorman, Meta-Analysis of Single-Case Research. T.M. Beasley, D.B. Allison, B.S. Gorman, The Potentially Confounding Effects of Cyclicity: Identification, Prevention, and Control. D.B. Allison, J.M. Silverstein, B.S. Gorman, Power, Sample Size Estimation, and Early Stopping Rules.