Design and Analysis of Single-Case Research

By Ronald D. Franklin; David B. Allison et al. | Go to book overview

Preface

A few years ago, at a meeting of the American Psychological Association ( August, 1993), I was asked to be the discussant for a series of papers on new research designs for the analysis of single subject data. Some of these papers now appear as chapters in this book. For me, this was an unusual request for two reasons. First, I am a terrible discussant, often drifting far afield from the main topic of the papers at hand. Second, most of my previous research has centered on latent variable structural equation modeling of cognitive abilities using large population based sample ( McArdle, 1994). However, as these presenters soon found out, I also advocate the use of more basic models using single subjects. This apparent contradiction on my part requires some further explanation.

The statistical features of the "law of large numbers" are well-known to the contemporary psychologists. In my first college level stats class (circa 1969), I learned the dictum, "odd things happen more often in small samples." Even though this principle is often misunderstood (see Nisbett, 1983), I was sure psychologists were mainly concerned with finding reliable and replicable results, so this was essential knowledge. In later classes on experimental design I learned that the surest way to achieve significant results was to have a very large sample (N); I think this early training accounts for much of my behavior today.

But then I went to graduate school (circa 1973), and things became more complicated. In my very first class I learned that some people had actually written papers on the benefits of what they called N = 1 designs. I was outspoken at this statistical heresy and I paid the price: I was forced (by Dr. Harold Yuker) to read and write about papers by Dukes ( 1965) and Shapiro ( 1964), a really difficult article by Rozeboom ( 1971), and something fairly new by Gottman ( 1973). I became aware of the importance of the "idiographic versus nomothetic" approaches to construct validation, and I began to understand the central concerns of "generalization" ( Crunbach et al., 1972). Although I was respectful of clinical practice, I thought that people were so different

-vii-

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Design and Analysis of Single-Case Research
Table of contents

Table of contents

  • Title Page iii
  • Contents v
  • Preface vii
  • References x
  • Contributors xiii
  • List of Equations xix
  • 1: Introduction 1
  • Introduction 1
  • References 10
  • 2: Historical and Philosophical Foundations of Single-Case Research 13
  • References 39
  • 3: Measurement of Dependent Variables 41
  • References 84
  • APPENDIX: CONSTRUCTING CONFIDENCE INTERVALS FOR ICCS (FROM SHROUT & FLEISS, 1979) 90
  • 4: Treatment Integrity in Single-Subject Research 93
  • 5: Graphical Display and Visual Analysis1 119
  • Introduction 119
  • References 154
  • 6: Statistical Alternatives for Single-Case Designs 159
  • References 208
  • 7: Serial Dependency in Single-Case Time Series 215
  • Introduction 215
  • References 242
  • 8: Meta-Analysis of Single-Case Research 245
  • Introduction 245
  • SUMMARY 273
  • References 273
  • 9: The Potentially Confounding Effects of Cyclicity: Identification, Prevention, and Control 279
  • References 328
  • Appendix 334
  • 10: Power, Sample Size Estimation, and Early Stopping Rules 335
  • Introduction 335
  • SUMMARY 367
  • References 368
  • Author Index 373
  • Subject Index 383
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