Statistics for Applied Behavior Analysis Practitioners and Researchers

1st Edition - June 17, 2023
Authors: David J. Cox, Jason C. Vladescu
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 9 8 8 5 - 7
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 8 5 2 7 - 7

Professionals who provide services based on the principles of behavior are required to use evidence-based practices and to make data-based decisions regarding assessments and in… Read more

Statistics for Applied Behavior Analysis Practitioners and Researchers

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Professionals who provide services based on the principles of behavior are required to use evidence-based practices and to make data-based decisions regarding assessments and interventions. Doing so requires statistical literacy: competence in collecting, analyzing, interpreting and presenting aggregate quantitative data within or between subjects. Without statistical literacy, behavior analysts cannot take advantage of, or intelligently discuss, ongoing scientific developments around interventions for autism spectrum disorders (ASD). Statistics for Applied Behavior Analysis Practitioners and Researchers provides practical and useful content for individuals who work directly with, or supervise those who work directly with, individuals with ASD. This book introduces core concepts and principles of modern statistical analysis that behavior analysts will need to deliver and consume the larger scientific literature. The organization of the book follows the common sequence of decisions for collecting, describing and analyzing data associated with behavior analytic service delivery and research. By the end of the book, readers should be able to understand and accurately incorporate statistics in their assessment and intervention effects using statistics.

Cover image
Title page
Table of Contents
Copyright
About the series editor
About the authors
Series Foreword: Critical Specialities in Treating Autism and Other Behavioral Challenges
Purpose
Preface
What this book is (and isn’t)
Onward, Ho!
Chapter 1. The requisite boring stuff part I: Defining a statistic and the benefit of numbers
Abstract
Introduction
Defining a statistic
The benefits of numbers
Models and model building
Common myths and misconceptions about statistics
Statistics in applied behavior analysis
Chapter summary
References
Chapter 2. The requisite boring stuff part II: Data types and data distributions
Abstract
Introduction
Data types
Data distributions
Quick recap and resituating ourselves
References
Supplemental: Probability distribution equations
Chapter 3. How can we describe our data with numbers? Central tendency and point estimates
Abstract
Introduction
What is next on the agenda?
High-level overview of the why and the how
Common descriptions of central tendency
Examples of how reporting central tendency in applied behavior analysis can be fun
Percentage
Chapter summary
References
Chapter 4. Just how stable is responding? Estimating variability
Abstract
Introduction
Describing the spread of your data
Describing how well you know your measure of central tendency
Other flavors for describing variability in your data
Choosing and using measures of variance in applied behavior analysis
References
Supplemental: Why square the difference, and square root the final measure?
Chapter 5. Just how good is my intervention? Statistical significance, effect sizes, and social significance
Abstract
Introduction
Statistical significance
Effect sizes
Social significance
Chapter summary
References
Chapter 6. Oh, shoot! I forgot about that! Estimating the influence of uncontrolled variables
Abstract
Introduction
Situating this chapter in the broader analytic landscape
Models of behavior
Brief primer on interpreting models
Chapter summary
References
Chapter 7. How fast can I get to an answer? Sample size, power, and observing behavior
Abstract
Introduction
Enough is enough
Is the intervention effect I’m seeing real?
How do I know if I’ve accounted for the variables’ multiply controlling behavior?
When to decide when to stop: Variations on a theme
Chapter summary
References
Chapter 8. Wait, you mean the clock is always ticking? The unique challenges time adds to statistically analyzing time series data
Abstract
Introduction
Statistical analysis of time series data for single-case designs
Structured criteria
(Non)Overlap statistics
Effect size measures
Regression and classification modeling
Nested approaches to modeling
Chapter summary
References
Chapter 9. This math and time thing is cool! Time series decomposition and forecasting behavior
Abstract
Introduction
Time series analyses through a different lens
Time series decomposition
Forecasting behavior
Chapter summary
References
Chapter 10. I suppose I should tell someone about the fun I’ve had: Chapter checklists for thinking, writing, and presenting statistics
Abstract
Introduction
Checklist and questions to answer when writing/presenting about statistics
References
Chapter 11. Through the looking glass: Probability theory, frequentist statistics, and Bayesian statistics
Abstract
Introduction
It’s assumptions, all the way down
Probability theory
Frequentist approach
Bayesian approach
Chapter summary
Closing thoughts
References
Index

David J. Cox

David J. Cox, Ph.D., M.S.B., BCBA-D currently works as the VP of Data Science at RethinkFirst and is faculty at the Institute for Applied Behavioral Science at Endicott College. Dr. Cox has earned a M.S. in Bioethics from Union Graduate College; a PhD in behavior analysis from the University of Florida; a post-doctoral fellowship at the Behavioral Pharmacology Research Unit of Johns Hopkins University School of Medicine; and a post-doctoral fellowship at Insight! Data Science. Since 2014, Dr. Cox’s research and applied work has focused on how to effectively leverage technology, quantitative modeling, and artificial intelligence to ethically optimize behavioral health outcomes and clinical decision-making. Based on his individual and collaborative work, he has published 50+ peer-reviewed articles, three books, and 150+ presentations at scientific conferences.

Affiliations and expertise

Chief Data Officer, Behavioral Health Center of Excellence and Faculty of Behavior Analysis, Endicott College, Beverly, MA, USA

Jason C. Vladescu

Jason C. Vladescu, Ph.D., BCBA-D, NSCP, LBA (NY), is a Founding Partner at The Capstone Center and Professor in the Department of Applied Behavior Analysis at Caldwell University. Jason completed his pre-doctoral internship and post-doctoral fellowship at the University of Nebraska Medical Center’s Munroe-Meyer Institute. He has published 80+ peer-reviewed articles and book chapters spanning his research interests in early behavioral intervention for children with autism spectrum and related disorders, increasing the efficiency of academic instruction, staff and caregiver training, equivalence-class formation, and mainstream applications of behavior analysis. Jason is on the Science Board of the Association for Behavior Analysis International; the President-Elect of the New Jersey Association for Behavior Analysis; a member of the Autism Advisory Panel for the New Jersey Department of Education; and is a current or former Associate Editor for Behavior Analysis in Practice and Journal of Applied Behavior Analysis. He currently or previously served on the editorial board for Behavior Analysis: Research and Practice, Behavioral Interventions, The Analysis of Verbal Behavior, The Psychological Record, School Psychology, Behavioral Development, and the Journal of Applied Behavior Analysis. He was the 2020 recipient of the APA (Division 25) New Applied Researcher Award.

Affiliations and expertise

Associate Professor, Department of Applied Behavior Analysis, Caldwell University; Clinical Supervisor, Center for Autism and Applied Behavioral Analysis, Caldwell, NJ, USA

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