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st: simulation to derive power for GLM multiple regression


From   Jake <daedalus702@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: simulation to derive power for GLM multiple regression
Date   Tue, 9 Mar 2010 07:51:47 -0800 (PST)

Hello,

I am interested in learning details about how to conduct simulations to calculate power for a test of a single coefficient in a GLM (negative binomial) multiple regression model.  I am somewhat familiar with the relevant methods outlined by Feiveson (2002).  However, what I am curious about which Feiveson does not discuss is how best to simulate when there are k covariates, in addition to the coefficient of interest.  

I assume I would treat the covariates as fixed -- using the real (already collected) data in the simulation, in other words.  Then I imagine that I would simulate only the variable for the coefficient of interest.  I'm not certain of how to generate this random variable so that it would be (asymptotically) correlated with all of the other variables in specified ways.  I imagine I would use the cholesky method?  But many of the variables are not normally distributed -- some are dichotomous, etc.

I would appreciate any help that you might provide.



Thanks,

Jacob Felson
Assistant Professor
Dept. of Sociology
William Paterson University

Reference

Feiveson, A.H. 2002 "Power by simulation."  The Stata Journal 2: 107-124.
http://www.stata.com/support/faqs/stat/power.html


      
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