Simpson’s Paradox in the interpretation of “leaky pipeline” data
The traditional ‘leaky pipeline’ plots are widely used to inform gender equality policy and practice. Herein, we demonstrate how a statistical phenomenon known as Simpson’s paradox can obscure trends in gender ‘leaky pipeline’ plots. Our approach has been to use Excel spreadsheets to generate hypoth...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Walton Paul H. [verfasserIn] Walton Daniel J. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: International Journal for Transformative Research ; 3(2016), 2, Seite 7 volume:3 ; year:2016 ; number:2 ; pages:7 |
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| Links: |
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| DOI / URN: |
10.1515/ijtr-2016-0013 |
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DOAJ095915966 |
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The traditional ‘leaky pipeline’ plots are widely used to inform gender equality policy and practice. Herein, we demonstrate how a statistical phenomenon known as Simpson’s paradox can obscure trends in gender ‘leaky pipeline’ plots. Our approach has been to use Excel spreadsheets to generate hypothetical ‘leaky pipeline’ plots of gender inequality within an organisation. The principal factors, which make up these hypothetical plots, can be input into the model so that a range of potential situations can be modelled. How the individual principal factors are then reflected in ‘leaky pipeline’ plots is shown. We find that the effect of Simpson’s paradox on leaky pipeline plots can be simply and clearly illustrated with the use of hypothetical modelling and our study augments the findings in other statistical reports of Simpson’s paradox in clinical trial data and in gender inequality data. The findings in this paper, however, are presented in a way, which makes the paradox accessible to a wide range of people. |
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The traditional ‘leaky pipeline’ plots are widely used to inform gender equality policy and practice. Herein, we demonstrate how a statistical phenomenon known as Simpson’s paradox can obscure trends in gender ‘leaky pipeline’ plots. Our approach has been to use Excel spreadsheets to generate hypothetical ‘leaky pipeline’ plots of gender inequality within an organisation. The principal factors, which make up these hypothetical plots, can be input into the model so that a range of potential situations can be modelled. How the individual principal factors are then reflected in ‘leaky pipeline’ plots is shown. We find that the effect of Simpson’s paradox on leaky pipeline plots can be simply and clearly illustrated with the use of hypothetical modelling and our study augments the findings in other statistical reports of Simpson’s paradox in clinical trial data and in gender inequality data. The findings in this paper, however, are presented in a way, which makes the paradox accessible to a wide range of people. |
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The traditional ‘leaky pipeline’ plots are widely used to inform gender equality policy and practice. Herein, we demonstrate how a statistical phenomenon known as Simpson’s paradox can obscure trends in gender ‘leaky pipeline’ plots. Our approach has been to use Excel spreadsheets to generate hypothetical ‘leaky pipeline’ plots of gender inequality within an organisation. The principal factors, which make up these hypothetical plots, can be input into the model so that a range of potential situations can be modelled. How the individual principal factors are then reflected in ‘leaky pipeline’ plots is shown. We find that the effect of Simpson’s paradox on leaky pipeline plots can be simply and clearly illustrated with the use of hypothetical modelling and our study augments the findings in other statistical reports of Simpson’s paradox in clinical trial data and in gender inequality data. The findings in this paper, however, are presented in a way, which makes the paradox accessible to a wide range of people. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ095915966</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240413130354.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240413s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1515/ijtr-2016-0013</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ095915966</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJe9c62171de004ce4a5465a8d61e0eac1</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">LC8-6691</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Walton Paul H.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Simpson’s Paradox in the interpretation of “leaky pipeline” data</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The traditional ‘leaky pipeline’ plots are widely used to inform gender equality policy and practice. Herein, we demonstrate how a statistical phenomenon known as Simpson’s paradox can obscure trends in gender ‘leaky pipeline’ plots. Our approach has been to use Excel spreadsheets to generate hypothetical ‘leaky pipeline’ plots of gender inequality within an organisation. The principal factors, which make up these hypothetical plots, can be input into the model so that a range of potential situations can be modelled. How the individual principal factors are then reflected in ‘leaky pipeline’ plots is shown. We find that the effect of Simpson’s paradox on leaky pipeline plots can be simply and clearly illustrated with the use of hypothetical modelling and our study augments the findings in other statistical reports of Simpson’s paradox in clinical trial data and in gender inequality data. 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