It's generally a good idea to impute once (or as many times as you like until you conclude you get it right), and then to take that one set of imputed data (i.e., the one collection 5 or so imputed data sets) and run as many analysis models as you like from that starting point.
Gary--
Gary King - Albert
J. Weatherhead III University Professor - Director, IQSS -
Harvard University
On Sat, Oct 27, 2012 at 3:50 AM, N. Janz
<nj248@cam.ac.uk> wrote:
Dear all,
I have two questions and would be very grateful for your help:
1) Is there a problem with running imputations on different subsets of your full data set when I use the same variables in my models from different imputations?
2) Do I have to include lags in the imputation specification that I expect I 'might' use in my models (although I'm not sure yet)? For example, all independent variables 'might' be lagged one year to allow for their effect to 'spread' to the outcome variable. If I don't include them and decide to use lags after a first run of imputations, do I have to go back to Amelia, include the lags, and run it again?
Best,
Nicole
Nicole Janz, PhD Cand.
Lecturer at Social Sciences Research Methods Centre 2012/13
University of Cambridge
Department of Politics and International Studies
www.nicolejanz.de | nj248@cam.ac.uk | Mobile: +44 (0) 7905 70 1 69 4
Skype: nicole.janz
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