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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 open-source statistical programming language, written by the book's authors, Charles Auerbach and Wendy Zeitlin.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. This book also contains numerous tests of statistical significance, such as t-tests, chi-squares and the conservative dual criteria. Auerbach and Zeitlin guide readers through the analytical process based on the characteristics of their data. Several 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.SSD for R 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 (http://ssdanalysis.com) with a growing number of instructional videos and a blog to build a community of researchers interested in single-subject designs.
This book investigates the methodology for conducting single-subject data analysis using the specialized SSD for R software package. Charles Auerbach, a PhD-level researcher, provides a technical framework for applying statistical rigor to single-subject research designs common in social work, psychology, and medicine. The text bridges the gap between theoretical statistical analysis and practical application by utilizing the open-source R programming language to facilitate evidence-based treatment evaluation.
What You Will Find
Experts identify this as a unique resource that combines methodological instruction with a functional, free software tool for practitioners. Readers frequently note the utility of the accompanying website and instructional videos in supporting the technical density of the statistical procedures described.
Page Count:
168
Publication Date:
2014-07-02
Publisher:
Oxford University Press
ISBN-10:
0199343594
ISBN-13:
9780199343591
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