How Can Single-Case Data Be Analyzed? Software Resources, Tutorial, and Reflections on Analysis

The present article aims to present a series of software developments in the quantitative analysis of data obtained via single-case experimental designs (SCEDs), as well as the tutorial describing these developments. The tutorial focuses on software implementations based on freely available platform...

Full description

Saved in:
Bibliographic Details
Published inBehavior modification Vol. 41; no. 2; pp. 179 - 228
Main Authors Manolov, Rumen, Moeyaert, Mariola
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.03.2017
SAGE PUBLICATIONS, INC
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:The present article aims to present a series of software developments in the quantitative analysis of data obtained via single-case experimental designs (SCEDs), as well as the tutorial describing these developments. The tutorial focuses on software implementations based on freely available platforms such as R and aims to bring statistical advances closer to applied researchers and help them become autonomous agents in the data analysis stage of a study. The range of analyses dealt with in the tutorial is illustrated on a typical single-case dataset, relying heavily on graphical data representations. We illustrate how visual and quantitative analyses can be used jointly, giving complementary information and helping the researcher decide whether there is an intervention effect, how large it is, and whether it is practically significant. To help applied researchers in the use of the analyses, we have organized the data in the different ways required by the different analytical procedures and made these data available online. We also provide Internet links to all free software available, as well as all the main references to the analytical techniques. Finally, we suggest that appropriate and informative data analysis is likely to be a step forward in documenting and communicating results and also for increasing the scientific credibility of SCEDs.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0145-4455
1552-4167
1552-4167
DOI:10.1177/0145445516664307