Ssd For R An R Package For Analyzing Single Subject Data

Review "This work is short but, in spite of its brevity, Charles Auerbach and Wendy Zeitlin's book describes how to analyse single-subject data using their own package, SSD for R. They introduce its functions as well as providing advice on how to analyse baseline and intervention phase data." -- Paul Webb, The Royal Statistical Society "This book describes what single-subject data is, how to measure these data, how to collect these data, how to record these data in Excel or a spreadsheet, how to transfer the data from Excel to the SSD for R software package, and how to use this software in analyzing the collected data. It provides an excellent step-by-step approach with great clinically relevant examples and snapshots from the original software to help readers understand. This is an excellent book. It is a valuable resource for a basic understanding of single-subject research data analysis and it gives step-by-step instructions on when and how to access the SSD for R software package." --Vedang J Bhavsar, Doody's Health Sciences Book Review Product Description Single-subject research designs have been used to build evidence to the effective treatment of problems across various disciplines including social work, psychology, psychiatry, medicine, allied health fields, juvenile justice, and special education. This book serves as a guide for those desiring to conduct single-subject data analysis. The aim of this text is to introduce readers to the various functions available in SSD for R, a new, free, and innovative software package written in R, the robust open-source statistical programming language, written by the book's authors. SSD for R has the most comprehensive functionality specifically designed for the analysis of single-subject research data currently available. SSD for R has numerous graphing and charting functions to conduct robust visual analysis. Besides the ability to create simple line graphs, additional features are available to add mean, median and standard deviation lines across phases to help better visualize change over time. Graphs can be annotated with text. SSD for R also contains a wide variety of functions to conduct statistical analyses that have traditionally been conducted with single-subject data. These include numerous descriptive statistics and effect size functions as well as tests of statistical significance, such as t-tests, chi-squares and the conservative dual criteria. Finally, SSD for R has the capability of analyzing group-level data. The authors step readers through the analytical process based on the characteristics of their data. Numerous examples and illustrations are provided throughout to help readers understand the wide range of functions available in SSD for R and their application to data analysis and interpretation. This is the only book of its kind to describe single-subject data analysis while providing free statistical software to do so. Additionally, the authors have an active website with a growing number of instructional videos and a blog to build a community of researchers interested in single-subject designs. About the Author Dr. Auerbach is a full professor at Yeshiva University and a well-known research methodologist. In addition to SSD for R, Dr. Auerbach was the lead author of SINGWIN, a forerunner of SSD for R. He has published over 80 articles in peer-reviewed publications, and is also the author of multiple book chapters. Dr. Zeitlin Schudrich is an assistant professor at Yeshiva University's Wurzweiler School of Social Work where she teaches courses in single-subject research, statistics, evidence-based social work, child welfare, and cultural competence. Her work has been published in peer-reviewed journals, and she is a frequent presenter at nationally recognized conferences.