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st: multiple imputation when all the independent variables have no missing values
From
Mandy fu <[email protected]>
To
[email protected]
Subject
st: multiple imputation when all the independent variables have no missing values
Date
Fri, 5 Mar 2010 14:18:26 -0500
Dear all,
I met some difficulty of conducting multiple imputation for ordinal
categorical variables. It would be great if someone could give me some
suggestion.
The data set I have includes :
*450 observations totally
*204 ordinal variables (after imputation these 204 items are used to
calculate 5 scales, which are the dependent variables in the following
regressions) have missing values
* 4 independent variables (dummy variables) no
missing values at all
I used --ice-- and included all the 208 variables in the variable list
to be imputed using ologit.
I have two questions:
(1) When the independent variables have NO missing values and only the
variables used to calculate depended variables have missing values, is
it appropriate to use multiple imputation? I doubt I was off the right
track from the very beginning.
(2) If the answer to (1) is yes, I cannot understand why the computer
works unbelievably slowly when conducting the MI. It took 6 hours for
the computer to finish only 4 cycles and there are 6 cycles left (I
set cycle (10) m(5)).
Thanks for your time!
Sincerely,
Mandy Fu
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