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Combining p-values in replicated single-case experiments with multivariate outcome.

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Title: Combining p-values in replicated single-case experiments with multivariate outcome.
Authors: Solmi, Francesca (AUTHOR), Onghena, Patrick (AUTHOR)
Source: Neuropsychological Rehabilitation. Jul2014, Vol. 24 Issue 3/4, p607-633. 27p.
Subjects: Single subject research, Experimental design, Probability theory, Simulation methods & models, Distribution (Probability theory), Multivariate analysis
Abstract: Interest in combining probabilities has a long history in the global statistical community. The first steps in this direction were taken by Ronald Fisher, who introduced the idea of combining p-values of independent tests to provide a global decision rule when multiple aspects of a given problem were of interest. An interesting approach to this idea of combining p-values is the one based on permutation theory. The methods belonging to this particular approach exploit the permutation distributions of the tests to be combined, and use a simple function to combine probabilities. Combining p-values finds a very interesting application in the analysis of replicated single-case experiments. In this field the focus, while comparing different treatments effects, is more articulated than when just looking at the means of the different populations. Moreover, it is often of interest to combine the results obtained on the single patients in order to get more global information about the phenomenon under study. This paper gives an overview of how the concept of combining p-values was conceived, and how it can be easily handled via permutation techniques. Finally, the method of combining p-values is applied to a simulated replicated single-case experiment, and a numerical illustration is presented. [ABSTRACT FROM AUTHOR]
Copyright of Neuropsychological Rehabilitation is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Combining p-values in replicated single-case experiments with multivariate outcome.
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  Data: <searchLink fieldCode="AR" term="%22Solmi%2C+Francesca%22">Solmi, Francesca</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Onghena%2C+Patrick%22">Onghena, Patrick</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Neuropsychological+Rehabilitation%22">Neuropsychological Rehabilitation</searchLink>. Jul2014, Vol. 24 Issue 3/4, p607-633. 27p.
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  Data: <searchLink fieldCode="DE" term="%22Single+subject+research%22">Single subject research</searchLink><br /><searchLink fieldCode="DE" term="%22Experimental+design%22">Experimental design</searchLink><br /><searchLink fieldCode="DE" term="%22Probability+theory%22">Probability theory</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Distribution+%28Probability+theory%29%22">Distribution (Probability theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Multivariate+analysis%22">Multivariate analysis</searchLink>
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  Data: Interest in combining probabilities has a long history in the global statistical community. The first steps in this direction were taken by Ronald Fisher, who introduced the idea of combining p-values of independent tests to provide a global decision rule when multiple aspects of a given problem were of interest. An interesting approach to this idea of combining p-values is the one based on permutation theory. The methods belonging to this particular approach exploit the permutation distributions of the tests to be combined, and use a simple function to combine probabilities. Combining p-values finds a very interesting application in the analysis of replicated single-case experiments. In this field the focus, while comparing different treatments effects, is more articulated than when just looking at the means of the different populations. Moreover, it is often of interest to combine the results obtained on the single patients in order to get more global information about the phenomenon under study. This paper gives an overview of how the concept of combining p-values was conceived, and how it can be easily handled via permutation techniques. Finally, the method of combining p-values is applied to a simulated replicated single-case experiment, and a numerical illustration is presented. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Neuropsychological Rehabilitation is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/09602011.2014.881747
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      – Code: eng
        Text: English
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        PageCount: 27
        StartPage: 607
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      – SubjectFull: Single subject research
        Type: general
      – SubjectFull: Experimental design
        Type: general
      – SubjectFull: Probability theory
        Type: general
      – SubjectFull: Simulation methods & models
        Type: general
      – SubjectFull: Distribution (Probability theory)
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      – SubjectFull: Multivariate analysis
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              Text: Jul2014
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