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st: testing for mediation


From   [email protected]
To   [email protected]
Subject   st: testing for mediation
Date   16 Jul 2009 06:59:02 -0500

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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