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Variance Inflation Factor [message #11698] 
Mon, 30 January 2017 19:21 
nwegbus
Messages: 15 Registered: December 2015

Member 


I'm working with the domestic violence module of Nigeria DHS (2013) using Stata 13.
I'm trying to examine my predictor variables for collinearity using the VIF score. Please see the attached document for all the output (you might want to zoom to 125%).
Here;s a summary of what I did:
I weighted my data using the following command:
generate wgt5 = d005/1000000
svyset [pweight = wgt5],psu(v021) strata(v022) singleunit(centered)
Then I ran a regression model of my predictor variables using this command:
svy: logit exipv agemarr4 religion weduc say attwb wipv polyg hseek chcomm
Then I issued the VIF command:
display "tolerance = " 1e(r2) " VIF = " 1/(1e(r2))
However this is the output I got:
tolerance = . VIF = .
It seems that the tolerance and VIF are missing? I'm wondering what I'm doing wrong, as I don't know what to make of a missing VIF score. Thanks in advance for your help.
SN





Re: Variance Inflation Factor [message #11717 is a reply to message #11715] 
Fri, 03 February 2017 09:27 
BridgetteDHS
Messages: 2314 Registered: February 2013

Senior Member 


Another response from Tom Pullum:
This question or problem goes beyond what we would normally give advice on. If I were in your situation, I would try to do the backward selection with successive reductions of the svy adjustments, until (hopefully!) it worked. That is, first remove the stratum adjustment, and try it. If it still doesn't work, remove the cluster adjustment, and try it. If it still doesn't work, remove the weight adjustment, and try it. I HOPE that at one stage of this process, at least the final one (with no svy adjustments at all) the procedure will work.
When you include all of the svy adjustments, the models are not fitted with maximumlikelihood methods. The measures of fit and the optimization of fit are not as solid as with ML (at least that's my understanding). However, I think that model selection procedures are fairly robust with respect to inclusion/omission of the svy adjustments. Plus, my general strategy when running into a complex problem is to simplify, simplify, simplify, until I get a strategy or a solution! That's all I can suggest.




Re: Variance Inflation Factor [message #12233 is a reply to message #11719] 
Thu, 13 April 2017 15:25 
bakerchowdhury
Messages: 21 Registered: April 2014

Member 


Hi,
I see VIF for SVY command gives us an overall tolerance for the model. However, I am wondering if there a way of calculating VIF for each predictor variable in SVY command (i.e. more like the VIF command under normal regression)?
Thank you
Baker




Re: Variance Inflation Factor [message #12654 is a reply to message #12233] 
Wed, 28 June 2017 14:03 
AnvitaDixit
Messages: 7 Registered: June 2017 Location: usa

Member 


Hi Baker, did you find a solution? Im having the same problem and would really appreciate if you could share how you got to individual VIFs for your independent variable in the model. Thanks!



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