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The Importance of Nonparametric Statistics in Mixed Methods Research Studies: Implications for Rigor and Ethicality.

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Title: The Importance of Nonparametric Statistics in Mixed Methods Research Studies: Implications for Rigor and Ethicality.
Authors: Leech, Nancy L.1 nancy.leech@ucdenver.edu, Onwuegbuzie, Anthony J.2,3,4
Source: International Journal of Multiple Research Approaches. 2020, Vol. 12 Issue 2, p135-152. 18p.
Subject Terms: *Statistical correlation, *Research methodology, *Data analysis, Conceptual structures, Nonparametric statistics, Research ethics, Serial publications
Abstract: The purpose of this editorial is to advocate for increased use of nonparametric statistics in mixed methods research studies, or more aptly labeled as mixed research to denote the fact that more than methods typically are mixed (e.g., philosophical assumptions and stances, research questions). First, we outline how the strengths of using nonparametric statistics outweighs the limitations. Second, we demonstrate empirically how infrequently nonparametric statistics appear in a flagship journal (i.e., Journal of Mixed Methods Research [JMMR]). We document that relatively few JMMR authors use nonparametric analyses to analyze qualitative data. Third, we provide a heuristic example from the extant literature to exemplify the use of nonparametric statistics in mixed research studies. Finally, we introduce a meta-framework for using nonparametric statistics in mixed research studies. Our article contributes to the mixed research literature by promoting increased rigor in particular and ethicality in general during the mixed analysis process. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Multiple Research Approaches is the property of Dialectical Publishing 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: Education Research Complete
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Multiple+Research+Approaches%22">International Journal of Multiple Research Approaches</searchLink>. 2020, Vol. 12 Issue 2, p135-152. 18p.
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  Data: *<searchLink fieldCode="DE" term="%22Statistical+correlation%22">Statistical correlation</searchLink><br />*<searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br />*<searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Conceptual+structures%22">Conceptual structures</searchLink><br /><searchLink fieldCode="DE" term="%22Nonparametric+statistics%22">Nonparametric statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Research+ethics%22">Research ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Serial+publications%22">Serial publications</searchLink>
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  Data: The purpose of this editorial is to advocate for increased use of nonparametric statistics in mixed methods research studies, or more aptly labeled as mixed research to denote the fact that more than methods typically are mixed (e.g., philosophical assumptions and stances, research questions). First, we outline how the strengths of using nonparametric statistics outweighs the limitations. Second, we demonstrate empirically how infrequently nonparametric statistics appear in a flagship journal (i.e., Journal of Mixed Methods Research [JMMR]). We document that relatively few JMMR authors use nonparametric analyses to analyze qualitative data. Third, we provide a heuristic example from the extant literature to exemplify the use of nonparametric statistics in mixed research studies. Finally, we introduce a meta-framework for using nonparametric statistics in mixed research studies. Our article contributes to the mixed research literature by promoting increased rigor in particular and ethicality in general during the mixed analysis process. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of International Journal of Multiple Research Approaches is the property of Dialectical Publishing 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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        Text: English
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      – SubjectFull: Statistical correlation
        Type: general
      – SubjectFull: Research methodology
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      – SubjectFull: Data analysis
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      – SubjectFull: Conceptual structures
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      – SubjectFull: Nonparametric statistics
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      – SubjectFull: Research ethics
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              Text: 2020
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