Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

st: Multiple Imputation (MI)

From   "Saul G. Alamilla" <>
To   Statalist <>
Subject   st: Multiple Imputation (MI)
Date   Mon, 13 May 2013 19:06:28 -0700 (PDT)

Dear Statalist Members,

I have some questions pertaining to multiple imputation. I have a
dataset of about 10,000 individuals and need to impute some variables with
considerable missingess (MAR). I am using the ice and mi commands in Stata 11.2

I plan to include substantive interactions terms (mean centered) in the
imputation model.

My questions/concerns are as follows:

1) Does mean centering need to be performed before imputing
data?  If so, because after imputation
the "centered" means will almost surely not be 0, would it be
advisable to center yet again at that point?

2) Is there a satisfactory way to impute interaction terms? Are
there any specific references regarding imputation and interaction terms (other
than articles such as Graham, 2009, which deals with interactions in passing)?
One approach would be to impute each of the input variables
individually and then take their product, but the imputing of the input
variables is especially delicate inasmuch as nonlinearities are introduced.

3. On a side note, are they any satisfactory ways to perform MI in
Stata with clustered data. I am aware of programs such as PAN (Schafer 2001,
Schafer & Yucel 2002), but am looking for MI commands or programs in Stata
geared for clustered/nested data, OR acceptable and manageable strategies for
imputing with such data.

Thanks in advance,

*   For searches and help try:

© Copyright 1996–2017 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index