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From |
Philip Ender <ender97@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Would _sgmediation_ work for dichotomous dependent variable? |

Date |
Sun, 1 Aug 2010 22:31:56 -0700 |

Bo MacInnis <bo@macinnis.org> wrote: Another question on effect size: I am an economist and trained in being interested in marginal effects rather than coefficients in the nonlinear model like logit or probit but I am working on a project for a psychologist. Would the mediational analysis be extended to marginal effect rather than coefficients in the probit model? e.g., the marginal effect of X on Y is mfx_c, the marginal effect of mediator M on Y is mfx_b, and the marginal effect of X on mediator M is mfx_a, would it make sense if I calculate the effect size based on the ratio of these marginal effects, rather than coefficients? ----- One way of estimating indirect effects for OLS regression to use the product of coefficients method. David Kenny (http://davidakenny.net/cm/mediate.htm) discusses a method for using the product of coefficients for models with dichotomous variables. One of the concerns for these types of models is that OLS coefficients are scaled very differently from logit or probit coefficients. -binary_mediation- accounts for this by standardizing all of the variables. Continuous variables are standardized in the normal way while the binary variables are standardized using the variances of the latent variables. So yes, standardization is required for this approach. I don't think the product of coefficients approach generalizes the marginal effects. I should also point out that -binary_mediation- does not directly compute standard errors like -sgmediation- but makes use of the the bootstrap command. -- Phil Ender UCLA Statistical Consulting Group * * 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/

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