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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