# RE: st: corcor

 From "Nick Cox" To Subject RE: st: corcor Date Tue, 10 Mar 2009 15:05:43 -0000

```Correlations are often awkward to deal with. Manifestly their bounds are [-1,1] and those bounds can bite.

A different handle on your question might to be look at confidence intervals. There is machinery in -corrci- from the Stata Journal.

SJ-8-3  pr0041  .  Speaking Stata: Corr. with confidence, Fisher's z revisited
(help corrci, corrcii if installed) . . . . . . . . . . . .  N. J. Cox
Q3/08   SJ 8(3):413--439
reviews Fisher's z transformation and its inverse, the
hyperbolic tangent, and reviews their use in inference
with correlations

Nick
n.j.cox@durham.ac.uk

Maarten buis

--- On Tue, 10/3/09, jasonm@ucla.edu <jasonm@ucla.edu> wrote:
> Are there any functions like corcor (H0:
> cor(x1x2)=cor(x1x3)) that test
> cor(x1x2)=cor(x3x4)?

A rather roundabout way of doing that (and others may come up
with much smarter solutions) is to use the fact that the
correlation is the bivariate regression coeficient when both
the dependent and independent variable have been standardized:

*-------------- begin example ----------------------
sysuse auto, clear
corr mpg weight displacement

local vars "mpg weight displacement"
foreach var of varlist `vars' {
sum `var'
gen double z_`var' = (`var'-r(mean))/r(sd)
}
reg z_mpg z_weight
est store a

reg z_mpg z_displacement
est store b

suest a b
test [a_mean]_b[z_weight] = [b_mean]_b[z_displacement]
lincom [a_mean]_b[z_weight] - [b_mean]_b[z_displacement]
*-------------------- end example ------------------------
(For more on how to use examples I sent to the Statalist, see
http://home.fsw.vu.nl/m.buis/stata/exampleFAQ.html )

*
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```