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Preface	p. xv
Epigram	p. xvii
The Single Case in Basic and Applied Research: An Historical Perspective	p. 1
Introduction	p. 1
Beginnings in Experimental Physiology and Psychology	p. 2
Origins of the Group Comparison Approach	p. 4
The influence of inferential statistics	p. 6
Development of Applied Research: The Case Study Method	p. 8
Early reports of percentage of success in treated groups	p. 10
The development of the group comparison approach in applied research	p. 11
Limitations of Early Group Comparison Approaches	p. 13
Ethical objections and practical problems	p. 13
Averaging of results	p. 14
Generality of findings	p. 14
Intersubject variability	p. 15
Early Alternative Approaches to Applied Research	p. 15
Naturalistic studies	p. 16
Process research	p. 18
The Scientist-Practitioner Split	p. 19
A Return to the Individual	p. 20
The role of the case study	p. 22
The representative case	p. 22
Shapiro's methodology in the clinic	p. 23
Quasi-experimental designs	p. 24
Chassan and intensive designs	p. 25
The Experimental Analysis of Behavior	p. 26
General Issues in a Single-Case Approach	p. 31
Introduction	p. 31
Variability	p. 32
Variability in basic research	p. 32
Variability in applied research	p. 33
Clinical vs. statistical significance	p. 34
Highlighting variability in the individual	p. 35
Repeated measures	p. 35
Rapidly changing designs	p. 36
Experimental Analysis of Sources of Variability Through Improvised Designs	p. 37
Subject fails to improve	p. 37
Subject improves "spontaneously"	p. 38
Subject displays cyclical variability	p. 40
Searching for "hidden" sources of variability	p. 41
Behavior Trends and Intrasubject Averaging	p. 42
Relation of Variability to Generality of Findings	p. 45
Generality of Findings	p. 46
Types of generality	p. 46
Problems in generalizing from a single-case	p. 47
Some Limitations of Group Designs in Establishing Generality of Findings	p. 48
Random sampling and inference in applied research	p. 48
Problems in generalizing from the group to the individual	p. 49
Improving generality of findings to the individual through homogeneous groups: logical generalization	p. 51
Homogeneous Groups Versus Replication of a Single-Case Experiment	p. 52
Direct replication and treatment/no-treatment control group design	p. 52
Systematic and clinical replication and factorial designs	p. 55
Blurring the Distinction Between Design Options	p. 57
General Procedures in Single-Case Research	p. 61
Introduction	p. 61
Repeated Measurement	p. 62
Practical implications and limitations	p. 62
Choosing a Baseline	p. 65
Baseline stability	p. 65
Examples of baselines	p. 67
Changing One Variable at a Time	p. 73
Correct and incorrect applications	p. 73
Exceptions to the rule	p. 74
Issues in drug evaluation	p. 80
Reversal and Withdrawal	p. 81
The reversal design	p. 82
Reversal and withdrawal designs compared	p. 83
Withdrawal of treatment	p. 83
Limitations and problems	p. 87
Length of Phases	p. 88
Individual and relative length	p. 88
Carryover effects	p. 91
Cyclic variation	p. 93
Evaluation of Irreversible Procedures	p. 94
Exceptions	p. 95
Assessing Response Maintenance	p. 97
Behavior Assessment	p. 99
Selection of Behavior to Assess	p. 102
Social significance	p. 102
Clinical significance	p. 104
Organizational significance	p. 104
Personal significance	p. 104
Measurement of Behavior	p. 105
Primary measures: behavioral dimensionals of proximal, directly observed behavior	p. 105
Temporality dimensions	p. 106
Repeatability dimensions	p. 107
Products of behavior	p. 110
Behavior rating scales	p. 111
Self-reports	p. 113
Physiological measures	p. 115
Settings for Assessment	p. 120
Contrived versus naturalistic settings and observations	p. 120
A continuum of contrivance	p. 121
Defining the behaviors to be observed	p. 124
Selecting observers	p. 125
Technically enhanced observation	p. 127
Training observers	p. 128
Reliability and validity	p. 129
The Assessment of Function	p. 131
Summary and Conclusions	p. 134
Basic A-B-A Withdrawal Designs	p. 135
Introduction	p. 135
Limitations of the case study approach	p. 135
A-B Design	p. 136
A-B with follow-up	p. 138
A-B with multiple target measures and follow-up	p. 140
A-B with follow-up and booster treatment	p. 142
A-B-A Design	p. 145
A-B-A from the adult literature	p. 146
A-B-A from child literature	p. 147
A-B-A-B Design	p. 149
A-B-A-B from child literature	p. 149
A-B-A-B when phase change is not under complete experimental control	p. 151
A-B-A-B with unexpected improvement in baseline	p. 153
A-B-A-B with monitoring of concurrent behaviors	p. 155
A-B-A-B with no feedback to experimenter	p. 156
B-A-B Design	p. 158
B-A-B with group data	p. 159
B-A-B from rogerian framework	p. 161
A-B-C-B Design	p. 162
A-B-C-B from the child literature	p. 163
A-B-C-B in a group application and follow-up	p. 164
Extensions of the A-B-A Design, Uses in Drug Evaluation and Interaction Design Strategies	p. 167
Extensions and Variations of the A-B-A Withdrawal Design	p. 167
A-B-A-B-A-B Design	p. 168
Comparing Separate Treatment Variables/Components	p. 169
A-B-A-C-A-C'-A design	p. 169
Parametric Variations of the Same Treatment Variable/Component	p. 172
A-B-A-B-B[subscript 1]-B[subscript 2]-B[subscript 3]-B[subscript N] design	p. 172
A-B- B[subscript 1]-B[subscript 2]-A-B[subscript 1] design	p. 173
Drug Evaluations	p. 175
Issues specific to drug evaluations	p. 176
Design options	p. 178
Strategies for Studying Interaction Effects	p. 185
Changing Criterion Designs	p. 198
Multiple Baseline Designs	p. 201
Introduction	p. 201
Multiple Baseline Designs	p. 202
Types of multiple baseline designs	p. 204
Multiple baseline design across behaviors	p. 205
Multiple baseline design across subjects	p. 218
Multiple baseline across settings	p. 228
Variations of Multiple Baseline Designs	p. 234
Nonconcurrent multiple baseline design	p. 234
Multiple-probe technique	p. 235
Issues in Drug Evaluations	p. 239
Alternating Treatments Design	p. 243
Introduction	p. 243
History and terminology	p. 245
Procedural Considerations	p. 246
Multiple-treatment interference	p. 247
Counterbalancing relevant experimental factors	p. 252
Number and sequencing of alternations	p. 253
Examples of Alternating Treatments Designs	p. 254
Comparing treatment and no treatment conditions	p. 254
Comparing multiple treatments	p. 258
Advantages of the Alternating Treatments Design	p. 266
Visual Analysis of the Alternating Treatments Designs	p. 267
Simultaneous Treatment Design	p. 268
Statistical Analyses for Single-Case Experimental Designs	p. 271
Introduction and Overview	p. 271
Single-Subject Experiments and Time-Series Data	p. 273
The nature of time-series data	p. 273
Mathematical and graphical description of a time series	p. 274
The problem of autocorrelation	p. 275
Autocorrelation and human behavior	p. 278
General comments	p. 279
Specific Statistical Tests	p. 279
Conventional t and F tests	p. 279
Randomization tests	p. 281
Interrupted time-series analysis (ITSA)	p. 287
Autoregressive Integrated Moving Average (ARIMA) Models	p. 288
Model building process	p. 291
Intervention (impact) analysis	p. 294
ITSA modeling strategies	p. 296
Box-Jenkins-Tiao strategy (Box & Tiao, 1965)	p. 296
Full series modeling strategy	p. 296
Interrupted time-series experiment (ITSE)	p. 297
Example	p. 298
Intervention analysis	p. 299
Other statistical tests	p. 301
Revusky's R[subscript n] (test of ranks)	p. 302
Split-middle technique	p. 302
Double bootstrap method	p. 303
Evaluation of statistical tests: which test to choose?	p. 303
Summary and Conclusion	p. 304
Beyond the Individual: Direct, Systematic, and Clinical Replication Procedures	p. 307
Introduction	p. 307
Direct Replication	p. 308
Definition of direct replication	p. 308
two successful replications	p. 309
four successful replications with design alterations during replications	p. 312
mixed results in a multiple baseline design	p. 316
simultaneous replication in a group	p. 319
Guidelines for direct replication	p. 321
Systematic Replication	p. 322
Definition of systematic replication	p. 322
Example: differential attention in children	p. 323
Comment on replication	p. 333
Guidelines for systematic replication	p. 333
Clinical Replication	p. 336
Definition of clinical replication	p. 337
Example: clinical replication with autistic children	p. 337
Benchmarking	p. 339
Practice Research Networks	p. 340
Advantages of Replication of Single-Case Experiments	p. 341
Hiawatha Designs an Experiment	p. 343
References	p. 347
Subject Index	p. 375
Name Index	p. 383
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Single Case Experimental Designs Strategies for Studying Behavior Change

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