Couldn't you get at least a reasonable estimate of the polychoric
correlation coefficient from -reoprob- (and the corresponding tetrachoric
correlation from -xtprobit-)? I'm not sure what the theoretical
relationship is between the expected value of rho reported by these commands
and the correlation coefficient of the underlying latent variable. They're
not synonymous, perhaps, but in the simulation below, using a simple case
for convenience (same number of categories--4--for both variables), rho
seems to be a suitable estimate of the correlation coefficient of the
underlying latent variable (the polychoric correlation coefficient).
Joseph Coveney
Mike Lacy wrote:
>It would be nice if someone could do a Stata package for polychoric
>correlations, which of course would include the tetrachoric case. The
>tetrac package, by its own admission, is not very accurate. There are some
>implementations out there (SPSS, Pascal, Fortran) that could be translated,
>with authors' permissions, of course.
----------------------------------------------------------------------------
clear
set more off
set seed 20040126
*
program define corho, rclass
version 8.2
tempvar dep rec ind cat
tempname cor A
drop _all
set obs 40
generate float `dep'1 = invnorm(uniform())
scalar `cor' = 0.4 + 0.4 * uniform()
generate float `dep'0 = `cor' * `dep'1 + ///
sqrt(1 - `cor' * `cor') * invnorm(uniform())
correlate `dep'*
return scalar cor = r(rho)
generate byte `rec' = _n
quietly reshape long `dep', i(`rec') j(`ind')
generate byte `cat' = 0
forvalues i = 1/3 {
replace `cat' = `cat' + (`dep' >= invnorm(`i' / 3))
}
capture reoprob `cat' `ind', i(`rec')
matrix `A' = e(b)
return scalar rho = `A'[1,4]
end
*
simulate "corho" cor = r(cor) rho = r(rho), reps(20)
regress rho cor
predict rho_hat, xb
/* predict rho_res, residuals
graph7 rho_res rho_hat, xlabel ylabel yline(0) */
graph7 rho rho_hat cor cor, xlabel ylabel sort ///
connect(.LL) symbol(Oii)
exit
*
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