Amelia March 2005

amelia@lists.gking.harvard.edu

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by daemon

19 years

TSCS imputation issues

by Strom C. Thacker

Hello, Some colleagues and I are trying to use Amelia to impute missing data in a time-series-cross-section (TSCS) dataset (what some might call a panel or pooled dataset). We have been able to run the imputation successfully, but we are getting somewhat odd results within countries. The results of our imputations produce means, standard deviations, etc. that are pretty consistent with our original data. That is, they seem to be pretty good "on average." But for this particular project, we are most interested in using these data for descriptive purposes, and especially to show trends over time within countries and groups of countries. The problem we are encountering is that we are getting some very odd results within each country's trend. For example, a country may have values that look like this in one of the imputed datasets: 30 [20.16830738] [47.24110787] [-15.5455354] [-35.74856172] 45.9 (Brackets indicate imputed values. These particular data are for telephone mainlines in Barbados from 1960 to 1965.) Later years show a clear increasing trend with less missing data, but these imputations are all over the place with respect to the time trend of the country. Our dataset has 8 variables (plus the country and year variables) and 7742 observations. Here are the options we used in the imputation: _AMcs=2 (our country ID) _AMts=1 (year variable) _AMtstep=1 _AMlagvs=10 (we arbitrarily chose one of our variables to lag) We have tried it setting _AMusets=1 and =0 and have gotten similar results either way. Does anyone have any suggestions or thoughts on this? Are we using Amelia incorrectly? Is it perhaps the wrong tool for this particular job? Thanks, Strom -- Strom C. Thacker Associate Professor of International Relations Director, Latin American Studies Program Boston University 152 Bay State Road Boston, MA 02215 Tel: 617.353.7160 Fax: 617.353.9290 sthacker(a)bu.edu http://www.bu.edu/sthacker/

19 years

how to report results generated by Amelia and other MI programs

by Patrick Egan

Hello: Have standards evolved regarding how to report results derived from imputed data generated by Amelia or other EM / MI methods? At a minimum, it seems that the analyst should report (or at least have readily available in appendix form): * the proportion of data missing on each variable in the original dataset, and the extent to which each variable is jointly observed with other variables * the variables used in the imputation models, and documentation that findings are robust to different imputation models * the number of datasets imputed and the estimated corresponding gain in efficiency (per Rubin 1987) * any ridge priors employed, and any changes to the convergence criteria used (e.g., changing the tolerance for convergence, or limiting the number of iterations of EM) What do Amelia's authors think of these criteria? Are there others we should be aware of? Or, alternately, is this overkill? Patrick Egan ---------------------------------------------------------------------- Patrick J. Egan Ph.D. Candidate Department of Political Science University of California, Berkeley http://socrates.berkeley.edu/~pjegan

19 years, 1 month

integrating amelia imputation without stata

by paul and penny

Hi all, I do not have a licence for stata to combine the imputations for amelia. I have thought about using an aggregate function in SPSS to generate means and standard deviations for cases across all the five files (My gut instinct is that this is way too simple). I have also thought about using NORM to combine the five file parameters (Again seems to simple). Any advice on how to combine the amelia data files without stata would be much appreciated. Kind regards Paul

19 years, 1 month

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Amelia March 2005