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st: RE: Multilevel models and multiple imputation

From   "Rodrigo Alfaro A." <>
To   <>
Subject   st: RE: Multilevel models and multiple imputation
Date   Tue, 11 Nov 2008 12:47:09 -0300



You could use combine option in -mim-. You should add the jacobian by
For example suppose that you want to have the log(mean of y):

mim, cat(combine) est(log(_b[_cons])) se(_se[_cons]/_b[_cons]): reg y 

HTH, Rodrigo.

-----Mensaje original-----
[] En nombre de Nailing Xia
Enviado el: Martes, 11 de Noviembre de 2008 11:48 a.m.
Asunto: st: Multilevel models and multiple imputation


I have a question regarding the standard error of the random-effects
parameter in multi-level models (-xtmixed).

I am estimating a multilevel model using -xtmixed-, and the dataset I
use is from multiple imputation procedure using -ice-. I use -mim- for
estimation and the command is : mim: xtmixed irtm pexpect pbelmth
mclsize mtexp if [parwgt] || schid: || childid:. The output gives the
random-effects paramters in logrithm of the paramters:
        irtm |     Coef.  Std. Err.        [95% Conf. Int.]   MI.df
   /lns1_1_1 |   1.20731   .052497                    1.10429  1.31034
   /lns2_1_1 |   2.42047   .009313                    2.40208  2.43886
    /lnsig_e   |   2.21744    .00496                     2.2077
2.22718  597.9

I know I can get the paramter by using di exp(1.20731), but how can I
get the corresponding standard errors?

Thank you!
Nailing Xia
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