If you're looking for an evaluation of mediation, check out -sgmediation- by Phil Ender, (e.g., findit sgmediation). This command computes the Sobel-Goodman mediation test.
-p
___________________________________
Paul F. Visintainer, PhD
Baystate Medical Center
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of [email protected]
Sent: Thursday, July 16, 2009 7:59 AM
To: [email protected]
Subject: st: testing for mediation
Dear Statalist members,
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
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* http://www.ats.ucla.edu/stat/stata/
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