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==Approaches to mediation==
 
==Approaches to mediation==
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While the concept of mediation as defined within psychology is theoretically appealing, the methods used to study mediation empirically have been challenged by statisticians and epidemiologists<ref name="Robins">{{cite journal | last1 = Robins | first1 = J. M. | author-link = James Robins | author-link2 = Sander Greenland | last2 = Greenland | first2 = S. | year = 1992 | title = Identifiability and exchangeability for direct and indirect effects |  journal = Epidemiology | volume = 3 | issue = 2| pages = 143–55 | doi = 10.1097/00001648-199203000-00013 | pmid = 1576220 }}</ref><ref name="Kaufman">{{cite journal|pmc=526390|doi=10.1186/1742-5573-1-4|year=2004|last1=Kaufman|first1=J. S.|title=A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation|journal=Epidemiologic Perspectives & Innovations |volume=1|issue=1|pages=4|last2=MacLehose|first2=R. F.|last3=Kaufman|first3=S|pmid=15507130}}</ref><ref name="Bullock">{{cite journal|pmid=20307128|url=http://www2.psych.ubc.ca/~schaller/528Readings/BullockGreenHa2010.pdf|year=2010|last1=Bullock|first1=J. G.|title=Yes, but what's the mechanism? (don't expect an easy answer)|journal=Journal of Personality and Social Psychology|volume=98|issue=4|pages=550–8|last2=Green|first2=D. P.|last3=Ha|first3=S. E.|doi=10.1037/a0018933}}
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Experimental approaches to mediation must be carried out with caution. First, it is important to have strong theoretical support for the exploratory investigation of a potential mediating variable.  
</ref> and interpreted formally.<ref name="Pearl-01">[[Judea Pearl|Pearl, J.]] (2001) [http://ftp.cs.ucla.edu/pub/stat_ser/R273-U.pdf "Direct and indirect effects"]. Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, [[Morgan Kaufmann]], 411&ndash;420.</ref>
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A criticism of a mediation approach rests on the ability to manipulate and measure a mediating variable. Thus, one must be able to manipulate the proposed mediator in an acceptable and ethical fashion. As such, one must be able to measure the intervening process without interfering with the outcome. The mediator must also be able to establish construct validity of manipulation.  
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One of the most common criticisms of the measurement-of-mediation approach is that it is ultimately a correlational design. Consequently, it is possible that some other third variable, independent from the proposed mediator, could be responsible for the proposed effect. However, researchers have worked hard to provide counter-evidence to this disparagement. Specifically, the following counter-arguments have been put forward:<ref name=CCWA/>
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(1) Experimental-causal-chain design
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(1) Temporal precedence. For example, if the independent variable precedes the dependent variable in time, this would provide evidence suggesting a directional, and potentially causal, link from the independent variable to the dependent variable.
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An experimental-causal-chain design is used when the proposed mediator is experimentally manipulated. Such a design implies that one manipulates some controlled third variable that they have reason to believe could be the underlying mechanism of a given relationship.
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(2) Nonspuriousness and/or no confounds. For example, should one identify other third variables and prove that they do not alter the relationship between the independent variable and the dependent variable he/she would have a stronger argument for their mediation effect. See other 3rd variables below.
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(2) Measurement-of-mediation design
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Mediation can be an extremely useful and powerful statistical test; however, it must be used properly. It is important that the measures used to assess the mediator and the dependent variable are theoretically distinct and that the independent variable and mediator cannot interact. Should there be an interaction between the independent variable and the mediator one would have grounds to investigate [[moderation (statistics)|moderation]].
 
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A measurement-of-mediation design can be conceptualized as a statistical approach. Such a design implies that one measures the proposed intervening variable and then uses statistical analyses to establish mediation. This approach does not involve manipulation of the hypothesized mediating variable, but only involves measurement.<ref>{{cite journal|pmid=16393019|url=http://www2.psych.ubc.ca/~schaller/528Readings/SpencerZannaFong2005.pdf|year=2005|last1=Spencer|first1=S. J.|title=Establishing a causal chain: Why experiments are often more effective than mediational analyses in examining psychological processes|journal=Journal of Personality and Social Psychology|volume=89|issue=6|pages=845–51|last2=Zanna|first2=M. P.|last3=Fong|first3=G. T.|doi=10.1037/0022-3514.89.6.845}}
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</ref>
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(1) Experimental-causal-chain design
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An experimental-causal-chain design is used when the proposed mediator is experimentally manipulated. Such a design implies that one manipulates some controlled third variable that they have reason to believe could be the underlying mechanism of a given relationship.
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(2) Measurement-of-mediation design
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A controlled version of the indirect effect does not
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间接效应的受控版本则不会
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A measurement-of-mediation design can be conceptualized as a statistical approach. Such a design implies that one measures the proposed intervening variable and then uses statistical analyses to establish mediation. This approach does not involve manipulation of the hypothesized mediating variable, but only involves measurement.<ref>{{cite journal|pmid=16393019|url=http://www2.psych.ubc.ca/~schaller/528Readings/SpencerZannaFong2005.pdf|year=2005|last1=Spencer|first1=S. J.|title=Establishing a causal chain: Why experiments are often more effective than mediational analyses in examining psychological processes|journal=Journal of Personality and Social Psychology|volume=89|issue=6|pages=845–51|last2=Zanna|first2=M. P.|last3=Fong|first3=G. T.|doi=10.1037/0022-3514.89.6.845}}
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exist because there is no way of disabling the  
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因为没有办法禁用
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</ref>
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direct effect by fixing a variable to a constant.
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把一个变量固定在一个常数上的直接效果。
      
==Criticisms of mediation measurement==
 
==Criticisms of mediation measurement==
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