Hi Michael,
I think you want to use the "noms" argument here. It will impute
observations in the set of observed values of the variable, as you want.
Hope that helps!
Cheers,
Matt
~~~~~~~~~~~
Matthew Blackwell
Assistant Professor of Government
Harvard University
url:
http://www.mattblackwell.org
On Sat, Nov 7, 2015 at 10:40 AM Neureiter, Michael <MIN24(a)pitt.edu> wrote:
Dear list members,
My name is Michael and I am a Ph.D. student in political science. I am
relatively new to Amelia, so I apologize if my question seems naïve to more
experienced users.
I am working with a large dataset based on survey responses. The data
includes a number of indices, which were created by taking the mean of
multiple survey items. For example, the index "group membership" takes the
average of six different types of groups a respondent can be a member of.
The values of this variable range from 1 to 3, with 21 unique values (1;
1.2; 1.25; 1.33; ...; 3).
My question is: How can I improve the imputation process so that Amelia
only uses these 21 values? As of right now, when I impute variables like
"group membership", Amelia generates a wide range of values that do not
make sense (negative values, values above three, etc.) given the initial
values and coding of these indices. I know how to do this with ordinal
variables, a.out <- amelia(data, m = 5, ords = "var name"), but
unfortunately I cannot figure out how to do a similar imputation-improving
transformation for indices such as "group membership".
I am using Amelia in R, so if anyone could give me the code to solve my
problem, I would much appreciate it. Thank you in advance for your help.
Best,
Michael
--
Amelia mailing list served by HUIT
[Un]Subscribe/View Archive:
http://lists.gking.harvard.edu/?info=amelia
More info about Amelia:
http://gking.harvard.edu/amelia
Amelia mailing list
Amelia(a)lists.gking.harvard.edu
To unsubscribe from this list or get other information:
https://lists.gking.harvard.edu/mailman/listinfo/amelia