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Article

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Accepted version

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2021-05-13

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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/184223

Quantitative techniques and graphical representations for interpreting results from alternating treatment design

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https://doi.org/10.1007/s40614-021-00289-9

Abstract

Multiple quantitative methods for single-case experimental design data have been applied to multiple-baseline, withdrawal, and reversal designs. The advanced data analytic techniques historically applied to single-case design data are primarily applicable to designs that involve clear sequential phases such as repeated measurement during baseline and treatment phases, but these techniques may not be valid for alternating treatment design (ATD) data where two or more treatments are rapidly alternated. Some recently proposed data analytic techniques applicable to ATD are reviewed. For ATDs with random assignment of condition ordering, the Edgington's randomization test is one type of inferential statistical technique that can complement descriptive data analytic techniques for comparing data paths and for assessing the consistency of effects across blocks in which different conditions are being compared. In addition, several recently developed graphical representations are presented, alongside the commonly used time series line graph. The quantitative and graphical data analytic techniques are illustrated with two previously published data sets. Apart from discussing the potential advantages provided by each of these data analytic techniques, barriers to applying them are reduced by disseminating open access software to quantify or graph data from ATDs.

Subject

Investigació de cas únic, Investigació quantitativa, Disseny d'experiments, Variables aleatòries

Subject (English)

Single subject research, Quantitative research, Experimental design, Random variables

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Articles publicats en revistes (Psicologia Social i Psicologia Quantitativa)

Citation

MANOLOV, Rumen, TANIOUS, René and ONGHENA, Patrick. Quantitative techniques and graphical representations for interpreting results from alternating treatment design. Perspectives on Behavior Science. 2021. Vol. 45, num. 1, pags. 259-294. ISSN 2520-8969. [consulted: 13 of August of 2026]. Available at: https://hdl.handle.net/2445/184223

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