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==Significance of mediation==
 
==Significance of mediation==
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<math>TE = E [Y(1) - Y(0)] </math>         
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(b) Controlled direct effect -
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(b)受管制的直接影响 -
      
As outlined above, there are a few different options one can choose from to evaluate a mediation model.
 
As outlined above, there are a few different options one can choose from to evaluate a mediation model.
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<math> CDE(m) = E [Y(1,m) - Y(0,m) ]  </math>
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(c) Natural direct effect -
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(c)天然直接效应 -
      
[[Bootstrapping (statistics)|Bootstrapping]]<ref>{{cite web |url=http://www.comm.ohio-state.edu/ahayes/sobel.htm |title=Testing of Mediation Models in SPSS and SAS |publisher=Comm.ohio-state.edu |access-date=2012-05-16 |archive-url=https://web.archive.org/web/20120518234943/http://www.comm.ohio-state.edu/ahayes/sobel.htm |archive-date=2012-05-18 |url-status=dead }}</ref><ref>{{cite web|url=http://www.comm.ohio-state.edu/ahayes/SPSS%20programs/indirect.htm |title=SPSS and SAS Macro for Bootstrapping Specific Indirect Effects in Multiple Mediation Models |publisher=Comm.ohio-state.edu |access-date=2012-05-16}}</ref> is becoming the most popular method of testing mediation because it does not require the normality assumption to be met, and because it can be effectively utilized with smaller sample sizes (''N''&nbsp;<&nbsp;25). However, mediation continues to be most frequently determined using the logic of Baron and Kenny <ref>[http://davidakenny.net/cm/mediate.htm "Mediation"]. ''davidakenny.net''. Retrieved April 25, 2012.</ref> or the [[Sobel test]]. It is becoming increasingly more difficult to publish tests of mediation based purely on the Baron and Kenny method or tests that make distributional assumptions such as the Sobel test. Thus, it is important to consider your options when choosing which test to conduct.<ref name=Hayes/>
 
[[Bootstrapping (statistics)|Bootstrapping]]<ref>{{cite web |url=http://www.comm.ohio-state.edu/ahayes/sobel.htm |title=Testing of Mediation Models in SPSS and SAS |publisher=Comm.ohio-state.edu |access-date=2012-05-16 |archive-url=https://web.archive.org/web/20120518234943/http://www.comm.ohio-state.edu/ahayes/sobel.htm |archive-date=2012-05-18 |url-status=dead }}</ref><ref>{{cite web|url=http://www.comm.ohio-state.edu/ahayes/SPSS%20programs/indirect.htm |title=SPSS and SAS Macro for Bootstrapping Specific Indirect Effects in Multiple Mediation Models |publisher=Comm.ohio-state.edu |access-date=2012-05-16}}</ref> is becoming the most popular method of testing mediation because it does not require the normality assumption to be met, and because it can be effectively utilized with smaller sample sizes (''N''&nbsp;<&nbsp;25). However, mediation continues to be most frequently determined using the logic of Baron and Kenny <ref>[http://davidakenny.net/cm/mediate.htm "Mediation"]. ''davidakenny.net''. Retrieved April 25, 2012.</ref> or the [[Sobel test]]. It is becoming increasingly more difficult to publish tests of mediation based purely on the Baron and Kenny method or tests that make distributional assumptions such as the Sobel test. Thus, it is important to consider your options when choosing which test to conduct.<ref name=Hayes/>
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<math>NDE = E [Y(1,M(0))  - Y(0,M(0))] </math>
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(d) Natural indirect effect
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(d)自然间接影响
      
==Approaches to mediation==
 
==Approaches to mediation==
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