SSD for R: An R Package for Analyzing Single-Subject Data, 2nd Edition
- Length: 224 pages
- Edition: 2
- Language: English
- Publisher: Oxford University Press
- Publication Date: 2021-11-12
- ISBN-10: 0197582753
- ISBN-13: 9780197582756
- Sales Rank: #3593613 (See Top 100 Books)
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. SSD for R serves as a guide for those
desiring to conduct single-subject data analysis and introduces 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 that was written by the book’s authors.
This second edition of SSD for R is the most comprehensive guide to the numerous graphing and charting functions for conducting robust visual analysis including line graphs and more complex standard deviation lines. 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. In addition to presentations and assignments, this new edition contains more examples and illustrations 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. For more instructional videos, blogs, and a growing community of researchers interested in single-subject designs, visit the authors’ website: http://ssdanalysis.com.
Cover Title Page Copyright Page Contents Introduction: Single-Subject Research Designs in the Behavioral and Health Sciences 1. Getting Your Data Into SSD for R 2. Overview of SSD for R Functions 3. Analyzing Baseline Phase Data 4. Comparing Baseline and Intervention Phases: Visualizing Your Findings and Descriptive Statistics 5. Statistical Tests of Type I Error 6. Analyzing Group Data 7. Meta-Analysis in Single-Subject Evaluation Research 8. Using RMarkdown to Present Your Findings 9. Building Support for Practice Research Appendix A: Entering and Editing Data Directly in R Appendix B: SSD for R Quick Functions Guide Appendix C: Decision Trees Appendix D: Bibliography of Additional Resources References Index
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