Hi Matissa, 

Currently, "lags" creates a lagged version of the original variable (not separated into a series of binary variables). The current value of the "noms" variable is the one that is broken up into a series of binary variables to impute them correctly. To do something more advanced, you may have to create the lags by hand---for instance, with a series of lagged binary indicators of the nominal variable. The same is true for multiple-period lags. 

Hope that helps!

Cheers,
matt.

~~~~~~~~~~~
Matthew Blackwell
Institute for Quantitative Social Science
Department of Government
Harvard University
url: http://www.mattblackwell.org

On Saturday, June 23, 2012 at 12:30 PM, Matissa Hollister wrote:

Hi,

I'm using Amelia on a panel dataset. The main variables that I'm imputing are nominal variables. I'd like to include lags/leads of those variables, since they are the best predictors of the missing values, but I'm not sure if the lags/leads option can handle nominal variables. I ran it and it didn't produce errors but the imputations were pretty far off (this is sort of simulated data, so there is a right answer, and the results here were not much better than random chance). At the moment I've changed the data to what stata calles "wide" format with one observation per individual and a separate variable for each year. This improves the imputations but I wonder whether I'm losing some of the predictive ability because I think the lag and lead are more predictive and I'd have a better estimate of these relationships with the larger sample size in "long" format that pools all of the ages.

Also, on a related note, is there a way to include double lags/leads (t-2, t+2)? I'm assuming this process is different from just creating a variable in the data that is the lag/lead and including it as a regular variable.

Thanks,

Matissa 
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