An Equivalence Testing Approach for Evaluating Substantial Mediation
In the past, researchers often used the nonsignificance of the direct path from the predictor to the outcome, in conjunction with a significant indirect effect, to make claims regarding \IeC {\textquoteleft }full mediation\IeC {\textquoteright }. However, the nil hypothesis (i.e., full mediation) is...
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| Autor*in: |
Beribisky, Nataly [verfasserIn] Mara, Constance A. [verfasserIn] Cribbie, Robert A. [verfasserIn] |
|---|
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E-Artikel |
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Englisch ; Französisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Tutorials in Quantitative Methods for Psychology - Université d'Ottawa, 2011, 16(2020), 5, Seite 424-441 |
|---|---|
| Übergeordnetes Werk: |
volume:16 ; year:2020 ; number:5 ; pages:424-441 |
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10.20982/tqmp.16.4.p424 |
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10.20982/tqmp.16.4.p424 doi (DE-627)DOAJ001589407 (DE-599)DOAJb0da744458e64a25b8f43fe397ddae50 DE-627 ger DE-627 rakwb eng fre BF1-990 Beribisky, Nataly verfasserin aut An Equivalence Testing Approach for Evaluating Substantial Mediation 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In the past, researchers often used the nonsignificance of the direct path from the predictor to the outcome, in conjunction with a significant indirect effect, to make claims regarding \IeC {\textquoteleft }full mediation\IeC {\textquoteright }. However, the nil hypothesis (i.e., full mediation) is not realistic and it is well known that a nonsignificant test statistic cannot be used to establish the accuracy of a research hypothesis. In this paper, we discuss equivalence testing based procedures for assessing when a mediator explains a substantial proportion of the relationship between a predictor and an outcome. Monte Carlo simulations are used to evaluate the performance of the proposed procedure and compare it against competing alternatives, including traditional tests of full mediation and a proportion mediated approach. The proposed equivalence testing based procedures and the proportion mediated approach performed similarly across the conditions investigated. Recommendations are provided for deciding among the approaches. mediation equivalence testing substantial mediation Psychology Mara, Constance A. verfasserin aut Cribbie, Robert A. verfasserin aut In Tutorials in Quantitative Methods for Psychology Université d'Ottawa, 2011 16(2020), 5, Seite 424-441 (DE-627)663846900 (DE-600)2616786-4 19134126 nnns volume:16 year:2020 number:5 pages:424-441 https://doi.org/10.20982/tqmp.16.4.p424 kostenfrei https://doaj.org/article/b0da744458e64a25b8f43fe397ddae50 kostenfrei https://www.tqmp.org/RegularArticles/vol16-5/p424/p424.pdf kostenfrei https://doaj.org/toc/1913-4126 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 16 2020 5 424-441 |
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In the past, researchers often used the nonsignificance of the direct path from the predictor to the outcome, in conjunction with a significant indirect effect, to make claims regarding \IeC {\textquoteleft }full mediation\IeC {\textquoteright }. However, the nil hypothesis (i.e., full mediation) is not realistic and it is well known that a nonsignificant test statistic cannot be used to establish the accuracy of a research hypothesis. In this paper, we discuss equivalence testing based procedures for assessing when a mediator explains a substantial proportion of the relationship between a predictor and an outcome. Monte Carlo simulations are used to evaluate the performance of the proposed procedure and compare it against competing alternatives, including traditional tests of full mediation and a proportion mediated approach. The proposed equivalence testing based procedures and the proportion mediated approach performed similarly across the conditions investigated. Recommendations are provided for deciding among the approaches. |
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In the past, researchers often used the nonsignificance of the direct path from the predictor to the outcome, in conjunction with a significant indirect effect, to make claims regarding \IeC {\textquoteleft }full mediation\IeC {\textquoteright }. However, the nil hypothesis (i.e., full mediation) is not realistic and it is well known that a nonsignificant test statistic cannot be used to establish the accuracy of a research hypothesis. In this paper, we discuss equivalence testing based procedures for assessing when a mediator explains a substantial proportion of the relationship between a predictor and an outcome. Monte Carlo simulations are used to evaluate the performance of the proposed procedure and compare it against competing alternatives, including traditional tests of full mediation and a proportion mediated approach. The proposed equivalence testing based procedures and the proportion mediated approach performed similarly across the conditions investigated. Recommendations are provided for deciding among the approaches. |
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BF1-990 |
| up_date |
2024-07-03T21:19:40.097Z |
| _version_ |
1803594319905423360 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ001589407</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230309163542.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230225s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.20982/tqmp.16.4.p424</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ001589407</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJb0da744458e64a25b8f43fe397ddae50</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><subfield code="a">fre</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">BF1-990</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Beribisky, Nataly</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="3"><subfield code="a">An Equivalence Testing Approach for Evaluating Substantial Mediation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</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">In the past, researchers often used the nonsignificance of the direct path from the predictor to the outcome, in conjunction with a significant indirect effect, to make claims regarding \IeC {\textquoteleft }full mediation\IeC {\textquoteright }. However, the nil hypothesis (i.e., full mediation) is not realistic and it is well known that a nonsignificant test statistic cannot be used to establish the accuracy of a research hypothesis. In this paper, we discuss equivalence testing based procedures for assessing when a mediator explains a substantial proportion of the relationship between a predictor and an outcome. Monte Carlo simulations are used to evaluate the performance of the proposed procedure and compare it against competing alternatives, including traditional tests of full mediation and a proportion mediated approach. The proposed equivalence testing based procedures and the proportion mediated approach performed similarly across the conditions investigated. 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7.4010954 |