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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/17644

Title: Combining p-values in replicated single-case experiments with multivariate outcome
Authors: SOLMI, Francesca
Onghena, Patrick
Issue Date: 2014
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.
Notes: [Solmi, Francesca] Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat, Diepenbeek, Belgium. [Onghena, Patrick] Katholieke Univ Leuven, Fac Psychol & Educ Sci, Leuven, Belgium.
URI: http://hdl.handle.net/1942/17644
DOI: 10.1080/09602011.2014.881747
ISI #: 000338032300017
ISSN: 0960-2011
Category: A1
Type: Journal Contribution
Validation: ecoom, 2015
Appears in Collections: Research publications

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