Re: st: testing for mediation

[scho0600@umn.edu]

Dear Dr. Buis,
Thank you so much for your prompt reply and help. I have been able to to 
download the ldecomp files for use.
I am still stuck because the predictor for which I wish to decompose total 
effects into direct and indirect is not categorical, but rather is a 
continuous normally distributed variable (as is the postulated mediating 
variable). If I have understood the ldecomp approach correctly, it works 
only when the predictor of interest is categorical.
Do you have any suggestions? I greatly appreciate your advice,

John Schousboe

On Jul 16 2009, Maarten buis wrote:

> Mediation is harder when dealing with non-linear models like -logit- than 
> in linear models, so the type of tricks you used below won't work in your 
> case. This is discussed in http://home.fsw.vu.nl/m.buis/wp/ldecomp.html , 
> which discusses one way of doing this test using -ldecomp-, which you can 
> download from SSC by typing in Stata -ssc install ldecomp-.
>
> Hope this helps,
> Maarten
>
> -----------------------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
>
> --- On Thu, 16/7/09, scho0600@umn.edu wrote:
>
> > I would be grateful for any assistance from anyone on
> > proper use of SUEST command to test for mediation of the
> > effect of one predictor on a dependent variable from another
> > predictor. To be clear, I wish to test for mediation, not
> > effect modification. I think x1 is a cause of y and x2 is
> > also a cause of y. I also know that x1 is a cause of x2. By
> > Barony and Kenney’s rules of mediation, one of the
> > necessary criteria to say that x2 mediates the effect of x1
> > on y is that the parameter estimate for x1 changes
> > significantly when x2 is added to the regression. The data I
> > have used is all from the same study sample.
> >
> > Here is the code I have used;
> > •    logit y x1 x2 x3
> > •    estimates store A
> > •    logit y x2 x3
> > •    estimates store B
> > •    suest A B
> > •    testnl [A]x1=[B]x2
> >
> > When I do this, the 95% confidence intervals of the
> > parameter estimates for x1 when x2 is or is not included
> > overlap considerably;
> > 0.23 (95% C.I. 0.01 to 0.46) when x2 is included, and
> > 0.33 (95% C.I. 0.11 to 0.54) when x2 is not included as a
> > predictor.
> >
> > And yet the chi-square and p-value for the test,
> > respectively, are 6.37 and 0.012. How can this test be
> > significant when the confidence intervals overlap so much?
> > Any ideas how I am misusing this test?
> >
> > I would appreciate any guidance or help anyone can give
> > me.
> >
> > John Schousboe MD, PhD
> >
> >
> > *
> > *   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/
>
>
>      
>
> *
> *   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/

*
*   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/