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st: Y standardization in ologit regressions with -mi-

From   "Daniel Escher" <>
To   <>
Subject   st: Y standardization in ologit regressions with -mi-
Date   Tue, 7 Dec 2010 09:03:00 -0500


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
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.

One post seems to suggest standardizing all the variables
Another recommends recommends examining intermediate results and pooling
them ( 

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. 

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