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This book is a practical resource designed for clinicians, researchers, and advanced students who wish to learn about single-case research designs. It covers the theoretical and methodological underpinnings of single-case designs, as well as their practical application in the clinical and research neurorehabilitation setting. The book briefly traces the history of single-case experimental designs (SCEDs); outlines important considerations in understanding and planning a scientifically rigorous single-case study, including internal and external validity; describes prototypical single-case designs (withdrawal-reversal designs and the medical N-of-1 trial, multiple-baseline designs, alternating-treatments designs, and changing-criterion designs) and required features to meet evidence standards, threats to internal validity, and strategies to address them; addresses data evaluation, covering visual analysis of graphed data, statistical techniques, and clinical significance; and provides a practical ten-step procedure for implementing single-case methods. Each chapter includes detailed illustrative examples from the neurorehabilitation literature. Novel features include: A focus on the neurorehabilitation setting, which is particularly suitable for single-case designs because of the complex and often unique presentation of many patients/clients. A practical approach to the planning, implementation, data analysis, and reporting of single-case designs. An appendix providing a detailed summary of many recently published SCEDs in representative domains in the neurorehabilitation field, covering basic and instrumental activities of daily living, challenging behaviours, disorders of communication and cognition, mood and emotional functions, and motor-sensory disabilities. It is valuable reading for clinicians and researchers in several disciplines working in rehabilitation, including clinical and neuropsychology, education, language and speech pathology, occupational therapy, and physical therapy. It is also an essential resource for advanced students in these fields who need a textbook for specialised courses on research methodology and use of single-case design in applied clinical and research settings.
This book is a practical guide to help researchers draw valid causal inferences from small-scale clinical intervention studies. It should be of interest to teachers of, and students in, courses with an experimental clinical component, as well as clinical researchers. Inferential statistics used in the analysis of group data are frequently invalid for use with data from single-case experimental designs. Even non-parametric rank tests provide, at best, approximate solutions for only some single-case (and small-n ) designs. Randomization (Exact) tests, on the other hand, can provide valid statistical analyses for all designs that incorporate a random procedure for assigning treatments to subjects or observation periods, including single-case designs. These Randomization tests require large numbers of data rearrangements and have been seldom used, partly because desktop computers have only recently become powerful enough to complete the analyses in a reasonable time. Now that the necessary computational power is available, they continue to be under-used because they receive scant attention in standard statistical texts for behavioral researchers and because available programs for running the analyses are relatively inaccessible to researchers with limited statistical or computing interest. This book is first and foremost a practical guide, although it also presents the theoretical basis for Randomization tests. Its most important aim is to make these tests accessible to researchers for a wide range of designs. It does this by providing programs on CD-ROM that allow users to run analyses of their data within a standard package (Minitab, Excel, or SPSS) with which they are already familiar. No statistical or computing expertise is required to use these programs. This is the "new stats" for single-case and small-n intervention studies, and anyone interested in this research approach will benefit.
This text ntroduces readers to the history, epistemology, and strategies of single-case research design. The authors offer concrete information on how to observe, measure, and interpret change in relevant outcome variables and how to design strategies that promote causal inferences. Key Features Includes case vignettes on specific single-case designs Describes clinical and applied case studies Draws on multiple examples of single-case designs from published journals across a wide range of disciplines Covers recent developments in applied research, including meta-analysis and the distinction between statistical and clinical significance Provides pedagogical tools to help readers master the material, including a glossary, interim summaries, end-of-chapter review questions, and activities that encourage active processing of material. Intended Audience This text is intended for students and practitioners in a variety of disciplines—including psychology, nursing, physical therapy, and occupational therapy—who are increasingly called upon to document the effectiveness of interventions.
Kazdin's text is a notable contrast to the quantitative methodology approach that pervades the biological and social sciences. The methodology in Single-Case Reasearch Designs focuses on a widely applicable methodology for evaluating interventions, such as treatment, or psychotherapy, using applied behavior anlaysis. However, this revision aims to encompass a broader range of research areas that utilize single-case designs. The text will convey the pertinence of this research methodology to disciplines ranging from psychology and medicine to business and industry. The first edition of this book, which was published in 1982, still sells a steady amount of copies today. The fact that professors continue to use the first edition of this book more than twenty years after it was published is a testament to the quality of information, organization, and narrative throughout the text. The possibility of a revision has professors excited that they can expose their students toa well-written, clear, and updated text that will reflect the current status of single-case research.
Single-Case Designs for Educational Research provides up-to-date in-depth information about the use of single-case experimental designs in educational research across a range of educational settings and students. Research Methods in Special Education. Appropriate for those pursuing advanced degrees in Education and Special Education.
Researchers often have difficulties collecting enough data to test their hypotheses, either because target groups are small or hard to access, or because data collection entails prohibitive costs. Such obstacles may result in data sets that are too small for the complexity of the statistical model needed to answer the research question. This unique book provides guidelines and tools for implementing solutions to issues that arise in small sample research. Each chapter illustrates statistical methods that allow researchers to apply the optimal statistical model for their research question when the sample is too small. This essential book will enable social and behavioral science researchers to test their hypotheses even when the statistical model required for answering their research question is too complex for the sample sizes they can collect. The statistical models in the book range from the estimation of a population mean to models with latent variables and nested observations, and solutions include both classical and Bayesian methods. All proposed solutions are described in steps researchers can implement with their own data and are accompanied with annotated syntax in R. The methods described in this book will be useful for researchers across the social and behavioral sciences, ranging from medical sciences and epidemiology to psychology, marketing, and economics.
It is particularly gratifying to prepare a second edition of a book, because there is the necessary impli cation that the first edition was well received. Moreover, now an opportunity is provided to correct the problems or limitations that existed in the first edition as well as to address recent developments in the field. Thus, we are grateful to our friends, colleagues, and students, as well as to the reviewers who have expressed their approval of the first edition and who have given us valuable input on how the revision could best be structured. Perhaps the first thing that the reader will notice about the second edition is that it is more extensive than the first. The volume currently has 41 chapters, in contrast to the 31 chapters that comprised the earlier version. Chapters 3, 9, 29, and 30 of the first edition either have been dropped or were combined, whereas 14 new chapters have been added. In effect, we are gratified in being able to reflect the continued growth of behavior therapy in the 1980s. Behavior therapists have addressed an ever-increasing number of disorders and behavioral dysfunctions in an increasing range of populations. The most notable advances are taking place in such areas as cognitive approaches, geriatrics, and behavioral medicine, and also in the treatment of childhood disorders.
Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest-posttest, nonequivalent groups, regression discontinuity, and interrupted time-series designs. He details their relative strengths and weaknesses and offers practical advice about their use. Reichardt compares quasi-experiments to randomized experiments and discusses when and why the former might be a better choice. Modern moethods for elaborating a research design to remove bias from estimates of treatment effects are described, as are tactics for dealing with missing data and noncompliance with treatment assignment. Throughout, mathematical equations are translated into words to enhance accessibility.
From award-winning author Gregory J. Privitera and Lynn Ahlgrim-Delzell, Research Methods for Education covers the different quantitative and qualitative research methods specific to their use in educational research. This new text uses a problem-focused approach that fully integrates the decision tree—from choosing a research design to selecting an appropriate statistic for analysis. With a conversational, student-friendly writing style, and examples from a wide variety of education-related fields, the authors show how methods and statistics work together and enable the testing of hypotheses through use of the scientific method. Students will become informed consumers of research with the ability to understand a research article, judge its quality and apply the methods in action research to inform educational practice. Give your students the SAGE edge! SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review, study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.