Re: st: RES: generating a variable with pre-specified correlations with other two (given) variables

[Richard Williams <richardwilliams.ndu@gmail.com>]

At 07:47 AM 8/31/2011, Tirthankar Chakravarty wrote:
> Throw in some orthogonal, zero mean noise when constructing Z:
>
> g z = .15625*x+.40625*y + runiform()

I believe that will zap the correlations though, won't it? i.e. the 
correlations of z with x and y will get smaller.

> > P.D. The reason I want to run the aforementioned regression is the
> > following. Suppose I have an initial regression of y on x, and x turns
> > out to be insignificantly different from zero at some chosen
> > confidence level. Then I want to generate an example in which adding a
> > new (artificial) variable z as a covariate I can get x to become
> > significantly different from zero at the same confidence level. Based
> > on the formula for the t-test, I think I can do this if I can control
> > the correlations between the artificial variable and the original
> > ones. The excercise is just for expositional purposes, I do not want
> > to attach any deep meaning to it.

If this is just for expositional purposes, it would probably be 
easier just to fake all the data with corr2data, rather than trying 
to create a combo of fake and real data. I think you could add a 
variable e that had 0 correlation with x and y and nonzero 
correlation with z. I generally find it is easier to get fake data to 
behave the way I want rather than real data.


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Richard Williams, Notre Dame Dept of Sociology
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