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From |
Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Wed, 31 Aug 2011 06:18:39 -0700 |

Yes, I meant -rnormal()-. Adding zero mean noise will, as Nick and Richard note, inflate the variance of Z (and so affect the correlations), but leave the covariances intact. T On Wed, Aug 31, 2011 at 6:14 AM, Nick Cox <njcoxstata@gmail.com> wrote: > Richard's question is the more crucial one, but I guess that > Tirthankar meant -rnormal()-. Adding -runiform()- will add 0.5 on > average (although that could easily be fixed). Either way, adding > noise will reduce the correlations. > > Nick > > On Wed, Aug 31, 2011 at 3:01 PM, Richard Williams > <richardwilliams.ndu@gmail.com> wrote: >> 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. > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- Tirthankar Chakravarty tchakravarty@ucsd.edu tirthankar.chakravarty@gmail.com * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: generating a variable with pre-specified correlations with other two (given) variables***From:*fjc <fjc120@gmail.com>

**st: RES: generating a variable with pre-specified correlations with other two (given) variables***From:*"Henrique Neder" <hdneder@ufu.br>

**Re: st: RES: generating a variable with pre-specified correlations with other two (given) variables***From:*Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com>

**Re: st: RES: generating a variable with pre-specified correlations with other two (given) variables***From:*fjc <fjc120@gmail.com>

**Re: st: RES: generating a variable with pre-specified correlations with other two (given) variables***From:*Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com>

**Re: st: RES: generating a variable with pre-specified correlations with other two (given) variables***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**Re: st: RES: generating a variable with pre-specified correlations with other two (given) variables***From:*Nick Cox <njcoxstata@gmail.com>

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