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

 From Richard Williams <[email protected]> To [email protected] Subject Re: st: Centering variables for interactions and using mi regress Date Sat, 15 Jan 2011 18:36:12 -0500

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.
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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.
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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.
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I am just sort of guessing with all this though; listen to the experts if they come forward!
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At 04:12 PM 1/15/2011, Amy S wrote:
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Hello everyone!Â This may be a very basic question for most of you, butÂ I am running regressions using multiple imputation (mi regress) in stata 11.Â Because my models have interactions, I need to center the continuous variables used in those interactions.Â However, I am unsure how to do this for the variable I am imputing.Â 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.Â However, because the missing data on the variable is imputed based on the regression model itself, I donât think I can do that.Â Please correct me if Iâm wrong, butÂ 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?Â 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?Â Maybe there is a simple way to do all of the centering and creatingÂ interaction terms and runnign the regression model with imputation allÂ in one stepÂ - I'm hoping so!Â Â Â
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-Amy

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Richard Williams, Notre Dame Dept of Sociology
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