Re: st: Centering variables for interactions and using mi regress

[Amy S <amylynns7@yahoo.com>]

Richard, Thanks for the advice and passing along Paul's previous advice on the subject! That is interesting - a little counterintuitive, but certainly easier to implement. 

I guess I will see if there are any other suggestions from the listserv in the meantime...

-Amy

--- On Sat, 1/15/11, Richard Williams <richardwilliams.ndu@gmail.com> wrote:

> From: Richard Williams <richardwilliams.ndu@gmail.com>
> Subject: Re: st: Centering variables for interactions and using mi  regress
> To: statalist@hsphsun2.harvard.edu
> Date: Saturday, January 15, 2011, 6:36 PM
> Interesting question, and I am not
> sure if there is any official wisdom on this.  One
> reason to center is so that 0 is a meaningful value. 
> For a variable like education, though, it might make sense
> to deduct 12 from each case, so that a score of 0 on the new
> variable corresponded to high school graduate. But in any
> event, if my life depended on it I think I would feel better
> doing the centering before imputation, rather than, say,
> have the centering be done differently with each
> imputation.
> 
> Also, I am not sure if this is a good idea, but I suppose
> you could run the analyses without centering, use the -mean-
> command to get the imputed mean for each variable, and then
> center using the imputed means.
> 
> As for the interactions, Paul Allison posted a while back
> that you should go ahead and compute interactions with the
> unimputed data and then let imputation fill in the missing
> values.  This may seem counter-intuitive, in that, say,
> if X1 has an imputed value of 3, and X2 has an imputed value
> of 7, the imputed value for the interaction X1X2 need not be
> 21! But Allison argued that you get biased results if you
> compute the interaction after X1 and X2 have been imputed.
> 
> I am just sort of guessing with all this though; listen to
> the experts if they come forward!
> 
> At 04:12 PM 1/15/2011, Amy S wrote:
> > Hello everyone!  This may be a very basic
> question for most of you, but I am running regressions
> using multiple imputation (mi regress) in stata 11. 
> Because my models have interactions, I need to center the
> continuous variables used in those interactions. 
> However, I am unsure how to do this for the variable I am
> imputing.  In the past, without multiple imputation,
> I have just centered the variables first, and then used the
> new centered variables (and interaction terms with those
> center variables) in the regression.  However,
> because the missing data on the variable is imputed based on
> the regression model itself, I donât think I can do
> that.  Please correct me if Iâm wrong, but  I
> doubt itâs legit to simply begin by centering the variable
> and then use mi regress to impute with the centered form of
> the variables, is it?  Even if that is legit, how
> would I create the interaction term before putting it into
> the regression if all the data
> >  has not been imputed yet and therefore there are
> missing variables?  Maybe there is a simple way to do
> all of the centering and creating interaction terms and
> runnign the regression model with imputation all in one
> step - I'm hoping so!  Â
> > Â
> > Thanks in advance!
> > Â
> > -Amy
> > 
> > 
> > 
> > 
> > 
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> 
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
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> 
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