1 / 21

An Introduction to Multiple Systems Estimation for Estimating a Count of Adverse Events

An Introduction to Multiple Systems Estimation for Estimating a Count of Adverse Events. Jana Asher Carnegie Mellon University October 16, 2002. Outline. Background Overview of capture-recapture Capture-recapture model assumptions Multiple systems estimation log-linear models

walter
Download Presentation

An Introduction to Multiple Systems Estimation for Estimating a Count of Adverse Events

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. An Introduction to Multiple Systems Estimation for Estimating a Count of Adverse Events Jana Asher Carnegie Mellon University October 16, 2002

  2. Outline • Background • Overview of capture-recapture • Capture-recapture model assumptions • Multiple systems estimation • log-linear models • Rasch models • Example • Ethnic Albanian deaths in Kosovo, March – June 1999

  3. Background • Used for estimating a population count. • The size of a wildlife population. • The number of WWW pages. • The number of people in the USA. • The number of human rights violations (civilian deaths) in Guatemala and Kosovo. • Capture-recapture = dual systems estimation. • Multiple capture-recapture = multiple systems estimation.

  4. Overview of Capture-Recapture Capture 1 Capture 2 Overlap

  5. Overview of Capture-Recapture

  6. Capture-Recapture Assumptions • Independence of lists • Homogeneity of capture probabilities • Error-free matching across lists • No in- or out-migration • No duplicates within a list • Lists are random samples

  7. Multiple Systems Estimation for Three Lists • Three lists allow for modeling of dependency and/or heterogeneity.

  8. Multiple Systems Estimation for Three Lists • Three lists allow for modeling of dependency and/or heterogeneity. • Model for dependency: where

  9. Multiple Systems Estimation for Three Lists • Three lists allow for modeling of dependency and/or heterogeneity. • Full quasi-symmetry (Rasch) model for heterogeneity: where

  10. Multiple Systems Estimation for Three Lists • Three lists allow for modeling of dependency and/or heterogeneity. • Full quasi-symmetry (Rasch) model for heterogeneity: Rasch model enables projection to missing cell via moment constraints (inequality restrictions).

  11. Multiple Systems Estimation for More than Three Lists • Same modeling techniques, more parameters. • More high-quality lists available means less assumptions are required.

  12. Example: Kosovo • Analysis required for the trial of former Yugoslav President Slobodan Milosevic for war crimes allegedly committed in Kosovo. • Question of interest: Did a systematic campaign by Yugoslav forces lead to Kosovar Albanian deaths and expel Kosovar Albanians from their homes?

  13. Example: Kosovo • Migration data from two sources; analyzed using standard demographic techniques. • Ethnic Albanian death data from four sources; estimates of number of deaths derived via multiple systems estimation.

  14. Kosovo: Data Sources • The American Bar Association Central and East European Law Initiative: 1,674 interviews; 5,089 incidents. • Exhumations by international teams on behalf of the International Criminal Tribunal for the Former Yugoslavia: 1,767 exhumations. • Human Rights Watch: 337 interviews; 1,717 incidents. • The Organization for Security and Cooperation in Europe: 1,837 interviews; one or more incidents each interview.

  15. Kosovo: Data Matching • Duplicates within each list removed. • 6 matches performed; one for each pair of lists. • Human coders used match-facilitation software. • Each list pair matched 2-4 times by different coders. • Number of individual deaths (killings where the victim can be named): 4,400.

  16. Kosovo: Data Matching

  17. Kosovo: Death Count Estimates • Estimate of overall number of deaths created from a log-linear model of the four-way cross-classification table: 10,356 (9,002, 12,122). • Two-day time period estimates of number of deaths created from log-linear models of three-way cross-classification tables; four such cross-classification tables per time period.

  18. Kosovo: Analysis

  19. Kosovo: Analysis • Regression analysis performed using KLA and NATO activity data as independent variables and death/migration estimates as dependent variables. • The analysis supports the conclusion that a systematic campaign of Yugoslav forces was responsible for ethnic Albanian migrations and deaths in Kosovo between March and June of 1999.

  20. Overall Conclusions • Where several high-quality pre-existing incomplete lists of adverse events exist, multiple systems estimation is a viable technique for estimating a total count of adverse events. • Relatively sophisticated technical expertise is required to use this estimation technique well.

  21. Further Reading • Ball, P., Betts, W., Scheuren, F., Dudukovich, J., and Asher, J. (2002). Killings and Refugee Flow in Kosovo March - June 1999: A Report to the International Criminal Tribunal for the Former Yugoslavia. American Association for the Advancement of Science, Washington, DC. • Contains a good reference list. • Available on my website: http://www.stat.cmu.edu/ ~asher/PAPERS2002/polkilkos_020109.pdf

More Related