Ssd for R An R Package For Analyzing Single-Subject Data
โ Scribed by Charles Auerbach, Wendy Zeitlin
- Publisher
- Oxford University Press
- Year
- 2014
- Tongue
- English
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
โฆ Table of Contents
Introduction: Single-Subject Research Designs in the Social 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. Building Support for Practice Research
References
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
โฆ Subjects
Data Analysis, R
๐ SIMILAR VOLUMES
Data Science for Infectious Disease Data Analytics: An Introduction with R provides an overview of modern data science tools and methods that have been developed specifically to analyze infectious disease data. With a quick start guide to epidemiological data visualization and analysis in R, this bo
Functional integration in the brain refers to distributed interactions among functionally segregated regions. Investigation of effective connectivity in brain networks, i.e, the directed causal influence that one brain region exerts over another region, is being increasingly recognized as an importa
Australian National University, 2001. โ 112 p.<div class="bb-sep"></div>R implements a dialect of the S language that was developed at AT&T Bell Laboratories by Rick Becker, John Chambers and Allan Wilks. Versions of R are available, at no cost, for 32-bit versions of Microsoft Windows for Linux, fo
<p><p>This book describes EnvStats, a new comprehensive R package for environmental statistics and the successor to the S-PLUS module EnvironmentalStats for S-PLUS (first released in 1997). EnvStats and R provide an open-source set of powerful functions for performing graphical and statistical analy
<p><p>This book describes EnvStats, a new comprehensive R package for environmental statistics and the successor to the S-PLUS module EnvironmentalStats for S-PLUS (first released in 1997). EnvStats and R provide an open-source set of powerful functions for performing graphical and statistical analy