Evaluation of treatment effect estimates in single‐case experimental research: comparison of twelve overlap methods and visual analysis.

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Title: Evaluation of treatment effect estimates in single‐case experimental research: comparison of twelve overlap methods and visual analysis.
Authors: Yucesoy‐Ozkan, Serife syucesoy@anadolu.edu.tr, Rakap, Salih, Gulboy, Emrah
Source: British Journal of Special Education. Mar2020, Vol. 47 Issue 1, p67-87. 21p. 5 Charts.
Subject Terms: *Special education, *Teaching, *Experimental methods in education, *Teaching methods, *Educational outcomes, *Data analysis, Single subject research, Effect sizes (Statistics)
Abstract: The purpose of this study was to compare 12 commonly‐used nonoverlap methods with each other and with the results of visual analysis. Data were obtained from 25 studies focused on embedded instruction and schema‐based instruction and included a total of 101 graphs. Treatment effect estimates using 12 nonoverlap methods were calculated for each graph by hand or using an online calculator. Five experts conducted visual analysis of each graph. Results showed that strong agreements existed between visual analysis and PND, TauNOVLAP and Tau‐U when raw data were analysed, and PND, PNCD and PEM‐T when categorised data were analysed. Of the 12 methods investigated, PND had the highest agreement rate with visual analysis, followed by PEM‐T, PAND, PNCD, IRD, NAP and TauNOVLAP. Overall, visual analysis appeared to be more conservative, as most nonoverlap methods overestimated the treatment effect. Additional research is needed to replicate and potentially validate the findings of this study. [ABSTRACT FROM AUTHOR]
Copyright of British Journal of Special Education is the property of Wiley-Blackwell 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.)
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  Data: <searchLink fieldCode="AR" term="%22Yucesoy‐Ozkan%2C+Serife%22">Yucesoy‐Ozkan, Serife</searchLink><i> syucesoy@anadolu.edu.tr</i><br /><searchLink fieldCode="AR" term="%22Rakap%2C+Salih%22">Rakap, Salih</searchLink><br /><searchLink fieldCode="AR" term="%22Gulboy%2C+Emrah%22">Gulboy, Emrah</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22British+Journal+of+Special+Education%22">British Journal of Special Education</searchLink>. Mar2020, Vol. 47 Issue 1, p67-87. 21p. 5 Charts.
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  Data: *<searchLink fieldCode="DE" term="%22Special+education%22">Special education</searchLink><br />*<searchLink fieldCode="DE" term="%22Teaching%22">Teaching</searchLink><br />*<searchLink fieldCode="DE" term="%22Experimental+methods+in+education%22">Experimental methods in education</searchLink><br />*<searchLink fieldCode="DE" term="%22Teaching+methods%22">Teaching methods</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+outcomes%22">Educational outcomes</searchLink><br />*<searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Single+subject+research%22">Single subject research</searchLink><br /><searchLink fieldCode="DE" term="%22Effect+sizes+%28Statistics%29%22">Effect sizes (Statistics)</searchLink>
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  Label: Abstract
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  Data: The purpose of this study was to compare 12 commonly‐used nonoverlap methods with each other and with the results of visual analysis. Data were obtained from 25 studies focused on embedded instruction and schema‐based instruction and included a total of 101 graphs. Treatment effect estimates using 12 nonoverlap methods were calculated for each graph by hand or using an online calculator. Five experts conducted visual analysis of each graph. Results showed that strong agreements existed between visual analysis and PND, TauNOVLAP and Tau‐U when raw data were analysed, and PND, PNCD and PEM‐T when categorised data were analysed. Of the 12 methods investigated, PND had the highest agreement rate with visual analysis, followed by PEM‐T, PAND, PNCD, IRD, NAP and TauNOVLAP. Overall, visual analysis appeared to be more conservative, as most nonoverlap methods overestimated the treatment effect. Additional research is needed to replicate and potentially validate the findings of this study. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of British Journal of Special Education is the property of Wiley-Blackwell 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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      – Type: doi
        Value: 10.1111/1467-8578.12294
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Teaching
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      – SubjectFull: Experimental methods in education
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      – SubjectFull: Teaching methods
        Type: general
      – SubjectFull: Educational outcomes
        Type: general
      – SubjectFull: Data analysis
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      – SubjectFull: Single subject research
        Type: general
      – SubjectFull: Effect sizes (Statistics)
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      – TitleFull: Evaluation of treatment effect estimates in single‐case experimental research: comparison of twelve overlap methods and visual analysis.
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            NameFull: Yucesoy‐Ozkan, Serife
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            NameFull: Rakap, Salih
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              Text: Mar2020
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              Y: 2020
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