Single Case Experimental Designs Strategies for Studying Behavior for Change

ISBN-10: 0205474551
ISBN-13: 9780205474554
Edition: 3rd 2009 (Revised)
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Description: "Single Case Experimental Designs" provides a clear and comprehensive introduction to the use of single case experimental designs. Single case experiments are a flexible and efficient type of research design that can be easily learned and used in  More...

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Book details

List price: $156.60
Edition: 3rd
Copyright year: 2009
Publisher: Allyn & Bacon, Incorporated
Publication date: 2/26/2008
Binding: Hardcover
Pages: 416
Size: 5.50" wide x 9.00" long x 1.00" tall
Weight: 1.518
Language: English

"Single Case Experimental Designs" provides a clear and comprehensive introduction to the use of single case experimental designs. Single case experiments are a flexible and efficient type of research design that can be easily learned and used in both scientific and practical settings to make causal inferences about the relations between an intervention or manipulation and change in the individual. The purpose of this book is to provide a comprehensive sourcebook on single case experimental designs with practical guidelines for their use in a range of research and clinical settings. It is suitable for use as a textbook for a course on research methodology or clinical assessment and treatment, or as a desk reference for seasoned researchers and practicing clinicians. Written in a non-technical style, this book is designed to be accessible to individuals from a range of backgrounds including advanced undergraduates, graduate students, researchers, and mental health practitioners-and to those working from a wide range of perspectives, including clinical psychology, educational or school psychology, social work, psychiatry, nursing, and other fields focused on human behavior change.

Matthew K. Nock is a Professor in the Department of Psychology, Harvard University, Cambridge, MA, USA.

Preface
Epigram
The Single Case in Basic and Applied Research: An Historical Perspective
Introduction
Beginnings in Experimental Physiology and Psychology
Origins of the Group Comparison Approach
The influence of inferential statistics
Development of Applied Research: The Case Study Method
Early reports of percentage of success in treated groups
The development of the group comparison approach in applied research
Limitations of Early Group Comparison Approaches
Ethical objections and practical problems
Averaging of results
Generality of findings
Intersubject variability
Early Alternative Approaches to Applied Research
Naturalistic studies
Process research
The Scientist-Practitioner Split
A Return to the Individual
The role of the case study
The representative case
Shapiro's methodology in the clinic
Quasi-experimental designs
Chassan and intensive designs
The Experimental Analysis of Behavior
General Issues in a Single-Case Approach
Introduction
Variability
Variability in basic research
Variability in applied research
Clinical vs. statistical significance
Highlighting variability in the individual
Repeated measures
Rapidly changing designs
Experimental Analysis of Sources of Variability Through Improvised Designs
Subject fails to improve
Subject improves "spontaneously"
Subject displays cyclical variability
Searching for "hidden" sources of variability
Behavior Trends and Intrasubject Averaging
Relation of Variability to Generality of Findings
Generality of Findings
Types of generality
Problems in generalizing from a single-case
Some Limitations of Group Designs in Establishing Generality of Findings
Random sampling and inference in applied research
Problems in generalizing from the group to the individual
Improving generality of findings to the individual through homogeneous groups: logical generalization
Homogeneous Groups Versus Replication of a Single-Case Experiment
Direct replication and treatment/no-treatment control group design
Systematic and clinical replication and factorial designs
Blurring the Distinction Between Design Options
General Procedures in Single-Case Research
Introduction
Repeated Measurement
Practical implications and limitations
Choosing a Baseline
Baseline stability
Examples of baselines
Changing One Variable at a Time
Correct and incorrect applications
Exceptions to the rule
Issues in drug evaluation
Reversal and Withdrawal
The reversal design
Reversal and withdrawal designs compared
Withdrawal of treatment
Limitations and problems
Length of Phases
Individual and relative length
Carryover effects
Cyclic variation
Evaluation of Irreversible Procedures
Exceptions
Assessing Response Maintenance
Behavior Assessment
Selection of Behavior to Assess
Social significance
Clinical significance
Organizational significance
Personal significance
Measurement of Behavior
Primary measures: behavioral dimensionals of proximal, directly observed behavior
Temporality dimensions
Repeatability dimensions
Products of behavior
Behavior rating scales
Self-reports
Physiological measures
Settings for Assessment
Contrived versus naturalistic settings and observations
A continuum of contrivance
Defining the behaviors to be observed
Selecting observers
Technically enhanced observation
Training observers
Reliability and validity
The Assessment of Function
Summary and Conclusions
Basic A-B-A Withdrawal Designs
Introduction
Limitations of the case study approach
A-B Design
A-B with follow-up
A-B with multiple target measures and follow-up
A-B with follow-up and booster treatment
A-B-A Design
A-B-A from the adult literature
A-B-A from child literature
A-B-A-B Design
A-B-A-B from child literature
A-B-A-B when phase change is not under complete experimental control
A-B-A-B with unexpected improvement in baseline
A-B-A-B with monitoring of concurrent behaviors
A-B-A-B with no feedback to experimenter
B-A-B Design
B-A-B with group data
B-A-B from rogerian framework
A-B-C-B Design
A-B-C-B from the child literature
A-B-C-B in a group application and follow-up
Extensions of the A-B-A Design, Uses in Drug Evaluation and Interaction Design Strategies
Extensions and Variations of the A-B-A Withdrawal Design
A-B-A-B-A-B Design
Comparing Separate Treatment Variables/Components
A-B-A-C-A-C'-A design
Parametric Variations of the Same Treatment Variable/Component
A-B-A-B-B[subscript 1]-B[subscript 2]-B[subscript 3]-B[subscript N] design
A-B- B[subscript 1]-B[subscript 2]-A-B[subscript 1] design
Drug Evaluations
Issues specific to drug evaluations
Design options
Strategies for Studying Interaction Effects
Changing Criterion Designs
Multiple Baseline Designs
Introduction
Multiple Baseline Designs
Types of multiple baseline designs
Multiple baseline design across behaviors
Multiple baseline design across subjects
Multiple baseline across settings
Variations of Multiple Baseline Designs
Nonconcurrent multiple baseline design
Multiple-probe technique
Issues in Drug Evaluations
Alternating Treatments Design
Introduction
History and terminology
Procedural Considerations
Multiple-treatment interference
Counterbalancing relevant experimental factors
Number and sequencing of alternations
Examples of Alternating Treatments Designs
Comparing treatment and no treatment conditions
Comparing multiple treatments
Advantages of the Alternating Treatments Design
Visual Analysis of the Alternating Treatments Designs
Simultaneous Treatment Design
Statistical Analyses for Single-Case Experimental Designs
Introduction and Overview
Single-Subject Experiments and Time-Series Data
The nature of time-series data
Mathematical and graphical description of a time series
The problem of autocorrelation
Autocorrelation and human behavior
General comments
Specific Statistical Tests
Conventional t and F tests
Randomization tests
Interrupted time-series analysis (ITSA)
Autoregressive Integrated Moving Average (ARIMA) Models
Model building process
Intervention (impact) analysis
ITSA modeling strategies
Box-Jenkins-Tiao strategy (Box & Tiao, 1965)
Full series modeling strategy
Interrupted time-series experiment (ITSE)
Example
Intervention analysis
Other statistical tests
Revusky's R[subscript n] (test of ranks)
Split-middle technique
Double bootstrap method
Evaluation of statistical tests: which test to choose?
Summary and Conclusion
Beyond the Individual: Direct, Systematic, and Clinical Replication Procedures
Introduction
Direct Replication
Definition of direct replication
two successful replications
four successful replications with design alterations during replications
mixed results in a multiple baseline design
simultaneous replication in a group
Guidelines for direct replication
Systematic Replication
Definition of systematic replication
Example: differential attention in children
Comment on replication
Guidelines for systematic replication
Clinical Replication
Definition of clinical replication
Example: clinical replication with autistic children
Benchmarking
Practice Research Networks
Advantages of Replication of Single-Case Experiments
Hiawatha Designs an Experiment
References
Subject Index
Name Index

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