RE: st: significant to non significant variable

["Ayayi, Ayi" <Ayi.Ayayi@uqtr.ca>]

Thanks  a lot Nick,
I reposted  the question because nobody answered  it and I was in the doubt that it didn't go through. 
Once again sorry for the inconvinience
-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
Sent: January-14-14 6:52 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: significant to non significant variable

You asked this question twice before.

http://www.stata.com/statalist/archive/2014-01/msg00344.html

http://www.stata.com/statalist/archive/2014-01/msg00340.html

Please see advice at
http://www.stata.com/support/faqs/resources/statalist-faq/#noanswer
and in particular the firm statement that you are allowed at most one repost.

In this case, despite your claim of "no collinearity", "no mu[lti]collinearity", it does seem likely that relationships among your predictors need closer scrutiny. Collinearity is not a yes-no property, but a matter of degree.

Also, I wouldn't make a fetish of significance. Sometimes, it is reasonable to include a predictor that is not significant at conventional levels in a model.

Perhaps you should look at

xtmixed y X1 X3 || country: || Microfinance

Perhaps X1, X2, X3 all should be included. Much depends on your economic grounds for including those predictors. With such anonymous names, I doubt that even conomists could comment on that choice.

Nick
njcoxstata@gmail.com


On 14 January 2014 11:36, Ayayi, Ayi <Ayi.Ayayi@uqtr.ca> wrote:
> - I have stata IC 10
> - I am conducting three-multilevel  analysis let say
>
>
> xtmixed y X1 X2 || country: || Microfinance . In this regression  X1 
> and X2 are statistically significant
>
> Now I add  X3  the regression becomes:
>
> xtmixed y X1 X2 X3|| country: || Microfinance
>
>  In this regression X2 is no longer significant. The same problem 
> arised when I add more than one variable
>
> I've checked for mulicollinearity among the variables with  VIF and 
> Collin and all the VIF . There is no  collinearity . All the ViF are 
> less than 2. So there is no mucollinearity
>
> Could you be please let me know what is the problem and how can I 
> handle it
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