Richard Williams wrote:
Here is how to get the same results in -oglm-. (oglm stands for
Ordinal Generalized Linear Models, but such models may be better know
by such names as location/scale models or heterogeneous choice
models. oglm was inspired by SPSS's PLUM routine but has some
Stata-ish features that PLUM does not.)
. webuse union
(NLS Women 14-24 in 1968)
. oglm union age black grade south, het(black)
[...]
lnsigma |
black | .0200207 .0693753 0.29 0.773 -.1159524 .1559938
-------------+---------------------------------------------------------------
/cut1 | 2.522383 .112186 22.48 0.000 2.302502 2.742263
------------------------------------------------------------------------------
. * Simple algebra converts log of sigma into Allison's delta
. scalar lnsigma = [lnsigma]_b[black]
. display "Allison's delta = " (1 - exp(lnsigma))/ exp(lnsigma)
Allison's delta = -.01982162
. * This reproduces the Wald test from Allison's procedure
. test [union]
( 1) [union]age = 0
( 2) [union]black = 0
( 3) [union]grade = 0
( 4) [union]south = 0
chi2( 4) = 1073.40
Prob > chi2 = 0.0000
I switched on the -eform- option in -estout- when in fact $\{delta}$ is conventionally measured in log-odds, but it was still -0.20 under -glogit- and 0.20 under -oglm-. However, your solution sorts that out, as well as the fit. Maybe you should incorporate it into the next version of -oglm-, Richard. That leaves my question (2) remaining.
Clive Nicholas
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