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From |
Jaime Gómez <jaime.gomez@unizar.es> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Mediating variables |

Date |
Sun, 5 Oct 2008 20:17:41 +0200 |

Dear Stata users I have a model in which the relationship between a predictor “x” and an outcome “y” is mediated by three factors (“r”, “s” and “t”). I am only able to test whether one of the predictors (“r”) mediates the relationship between “x” and “y” (I only have data on this mediating variable and I cannot get data on the other two). I would like to implement Baron and Kenny (1986)’s test for mediation. At least, this involves estimating the following system: Y=a1+b*r+c*x+epsilon1 r=a2+d*x+epsilon2 Given that the errors of the two equations are potentially correlated, it has been suggested that a 2SLS approach should be used. I have seen that this could be done with ivregress, provided that I can find data on at least one variable that affects “r” and does not affect “y”. My doubts are the following: 1) Given that I have a triangular system, do I have to use the traditional approach implemented by ivregress or the “modified” proposed in http://www.stata.com/support/faqs/stat/ivr_faq.html ? Are both valid? 2) How do I test for the hypothesis that the errors are correlated? I have seen that the use of a Hausman test is suggested in the literature, but I do not know how to implement this in Stata (specially in the case I use the “modified” approach) 3) Given that I have panel data, could I take advantage of the panel structure of my data to correct for the fact that I do not have information on two of the mediating variables (“s” and “t”)? Is there a procedure in Stata for that? Thanks a lot Jaime Gómez Universidad de Zaragoza * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Mediating variables***From:*John Antonakis <John.Antonakis@unil.ch>

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