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st: Collinearity in svy


From   "Simon, Alan (CDC/CCHIS/NCHS)" <fpa8@cdc.gov>
To   statalist@hsphsun2.harvard.edu
Subject   st: Collinearity in svy
Date   Fri, 2 May 2008 09:21:58 -0400

Hi all, 

I was wondering if anyone has any good ideas about how to measure
multicollinearity of variables in a complex survey design data set, when
many of the variables are categorical. 

There is some guidance on the UCLA website about how to do this when
variables are continuous, but I can't seem to use this approach with
categorical data. 

The website essentially suggests using each variable as a dependent
variable in a separate regression  using all other variables as
independent variables, and then using the following command: 

display "tolerance = " 1-e(r2) " VIF = " 1/(1-e(r2))  

to calculate the Variance inflation factor.  However, this only seems to
work if the dependent variable is continous and the regression is OLS. 

Is there a way to measure the variance inflation factor for categorical
variables in a complex survey design?  Or is there a better way to
approach this problem? 

Thanks, 

Alan 



Alan E. Simon
Medical Officer
Hospital Care Statistics Branch
Division of Health Care Statistics
National Center for Health Statistics
Centers for Disease Control and Prevention
(301) 458-4338
asimon2@cdc.gov

Rm. 3231
3311 Toledo Road
Hyattsville, MD  20782



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