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...
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Published in | Behavior modification Vol. 41; no. 2; pp. 179 - 228 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Los Angeles, CA
SAGE Publications
01.03.2017
SAGE PUBLICATIONS, INC |
Subjects | |
Online Access | Get full text |
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Abstract | 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. |
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AbstractList | 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.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. 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. |
Author | Moeyaert, Mariola Manolov, Rumen |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27553741$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Behavioral Research - methods Computer Software Data Analysis Data Interpretation, Statistical Humans Investigació de cas únic Numerical Analysis, Computer-Assisted - instrumentation Programari Research Design Researchers Single subject research Software Studies |
Title | How Can Single-Case Data Be Analyzed? Software Resources, Tutorial, and Reflections on Analysis |
URI | https://journals.sagepub.com/doi/full/10.1177/0145445516664307 https://www.ncbi.nlm.nih.gov/pubmed/27553741 https://www.proquest.com/docview/1867775368 https://www.proquest.com/docview/1859715782 https://recercat.cat/handle/2072/282328 |
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