st: Y standardization in ologit regressions with -mi-

["Daniel Escher" <descher@nd.edu>]

Hello,

I performed multiple imputation on a dataset in Stata 11.1 using -mi
impute-. My basic syntax for analysis is:
. mi est, post: ologit forgive sex age south i.race 

I would like to obtain standardized coefficients. In particular, I would
like to have Y-standardization so I can compare coefficients across models
as discussed in Long & Freese's book
(http://www.stata-press.com/books/regmodcdvs.html). 
1. Is that possible using -mi est-? 
2. Is there, perhaps, an mi equivalent to -listcoef-?

I am aware of -mibeta-; however, it works only with linear regressions.
(http://statalist.1588530.n2.nabble.com/multiple-imputation-td5535082.html#a
5536253)

One post seems to suggest standardizing all the variables
(http://www.stata.com/statalist/archive/2009-03/msg00115.html) 
Another recommends recommends examining intermediate results and pooling
them (http://www.stata.com/statalist/archive/2009-12/msg01004.html) 

The last one may be my best option, but I wouldn't obtain y* values. Before
I go down that road, is there an alternative? 

I am working with Stata 11.1 IC on Windows XP. 

*
*   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/