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st: RE: testing for mediation

From   "Visintainer PhD, Paul" <>
To   "''" <>
Subject   st: RE: testing for mediation
Date   Thu, 16 Jul 2009 13:19:43 -0400

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.


Paul F. Visintainer, PhD
Baystate Medical Center

-----Original Message-----
From: [] On Behalf Of
Sent: Thursday, July 16, 2009 7:59 AM
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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