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Technical Memo for Amnesty International Report on Deaths in Detention

Megan Price, Anita Gohdes and Patrick Ball (2016). Human Rights Data Analysis Group, commissioned by Amnesty International. August 17, 2016. © 2016 HRDAG. Creative Commons BY-NC-SA.

Statistics and Slobodan

Patrick Ball and Jana Asher (2002). “Statistics and Slobodan: Using Data Analysis and Statistics in the War Crimes Trial of Former President Milosevic.” Chance, vol. 15, No. 4, 2002. Reprinted with permission ofChance. © 2002 American Statistical Association. All rights reserved.

Welcoming Our New Statistician

Maria Gargiulo has joined HRDAG as a Statistician.

Learning the Hard Way at the ICTY: Statistical Evidence of Human Rights Violations in an Adversarial Information Environment.

Amelia Hoover Green. In Collective Violence and International Criminal Justice: An Interdisciplinary Approach, ed. Alette Smeulers, Antwerp, Belgium. © 2010 Intersentia. All rights reserved. [Link coming soon]

Quantifying Injustice

“In 2016, two researchers, the statistician Kristian Lum and the political scientist William Isaac, set out to measure the bias in predictive policing algorithms. They chose as their example a program called PredPol.  … Lum and Isaac faced a conundrum: if official data on crimes is biased, how can you test a crime prediction model? To solve this technique, they turned to a technique used in statistics and machine learning called the synthetic population.”

At Toronto’s Tamil Fest, human rights group seeks data on Sri Lanka’s civil war casualties

Earlier this year, the Canadian Tamil Congress connected with HRDAG to bring its campaign to Toronto’s annual Tamil Fest, one of the largest gatherings of Canada’s Sri Lankan diaspora.

Ravichandradeva, along with a few other volunteers, spent the weekend speaking with festival-goers in Scarborough about the project and encouraging them to come forward with information about deceased or missing loved ones and friends.

“The idea is to collect thorough, scientifically rigorous numbers on the total casualties in the war and present them as a non-partisan, independent organization,” said Michelle Dukich, a data consultant with HRDAG.

Data Mining for Good: CJA Drink + Think

At the Center for Justice and Accountability's happy hour, "Drink and Think," Patrick Ball spoke about "Data Mining for Good." The talk included a discussion of how HRDAG brings human rights abusers to justice through data analysis, and HRDAG's work conducting quantitative analysis for truth commissions, NGOs, the UN and other partners. The event was held at Eventbrite. More photos are below. The Center for Justice and Accountability Young Professionals' Committee for Human Rights September 16, 2014 San Francisco, California Link to CJA event page Back to Talks   All photos © 2014 Carter Brooks.

Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies

This Harvard Data Science Review article uses the least unreliable source of pandemic data: reported deaths.

Using Statistics to Assess Lethal Violence in Civil and Inter-State War

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application, Volume 6. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.

Low-risk population size estimates in the presence of capture heterogeneity

James Johndrow, Kristian Lum and Daniel Manrique-Vallier (2019). Low-risk population size estimates in the presence of capture heterogeneity. Biometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065

James Johndrow, Kristian Lum and Daniel Manrique-Vallier (2019). Low-risk population size estimates in the presence of capture heterogeneity. Biometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065

A Comparison of Marginal and Conditional Models for Capture–Recapture Data with Application to Human Rights Violations Data

Shira Mitchell, Al Ozonoff, Alan Zaslavsky, Bethany Hedt-Gauthier, Kristian Lum and Brent Coull (2013). A Comparison of Marginal and Conditional Models for Capture-Recapture Data with Application to Human Rights Violations Data. Biometrics, Volume 69, Issue 4, pages 1022–1032, December 2013. © 2013, The International Biometric Society. DOI: 10.1111/biom.12089.

Shira Mitchell, Al Ozonoff, Alan Zaslavsky, Bethany Hedt-Gauthier, Kristian Lum and Brent Coull (2013). A Comparison of Marginal and Conditional Models for Capture-Recapture Data with Application to Human Rights Violations Data. Biometrics, Volume 69, Issue 4, pages 1022–1032, December 2013. © 2013, The International Biometric Society. DOI: 10.1111/biom.12089.

Theoretical limits of microclustering for record linkage

James E Johndrow, Kristian Lum and D B Dunson (2018). Theoretical limits of microclustering for record linkage. Biometrika. 19 March 2018. © 2018 Oxford University Press. DOI 10.1093/biomet/asy003.

John E Johndrow, Kristian Lum and D B Dunson (2018). Theoretical limits of microclustering for record linkage. Biometrika. 19 March 2018. © 2018 Oxford University Press. DOI 10.1093/biomet/asy003.

A Model to Estimate SARS-CoV-2-Positive Americans

We’ve built a model for estimating the true number of positives, using what we have determined to be the most reliable datasets—deaths.

Emeritus Advisers

We are grateful to our past advisers for their contributions to HRDAG. Advisory Board Audrey Chapman, Healey Chair in Medical Humanities and Bioethics, University of Connecticut 2013-2014 (one-year term)

HRDAG Offers New R Package – dga

Much of the work we do at HRDAG involves estimating the number of undocumented deaths using a statistical technique called multiple systems estimation (MSE, described in more detail here). One of our goals is to make this class of methods more broadly available to human rights researchers. In particular, we are finding that Bayesian approaches are extremely valuable for MSE. Accordingly, we are pleased to offer a new R package called dga (“decomposable graphs approach”) that performs Bayesian model averaging for MSE. The main function in this package implements a model created by David Madigan and Jeremy York. This model was designed to ...

Overbooking’s Impact on Pre-Trial Risk Assessment Tools

How do police officer booking decisions affect tools relied upon by judges?

Update of Iraq and Syria Data in New Paper

This week The Statistical Journal of the IAOS published a new(ish) paper by Megan Price and Patrick Ball. The open-access paper, Selection bias and the statistical patterns of mortality in conflict, is a revisiting and updating of both the Iraq and Syria examples used in an earlier paper, Big Data, Selection Bias, and the Statistical Patterns of Mortality in Conflict, which was published last year inThe SAIS Review of International Affairs (JHU Press, 2014). HRDAG believes that the concerns highlighted by these examples are important for a wide variety of audiences, including both the foreign policy readers reached by The SAIS Review and the ...

Patrick Ball wins the Karl E. Peace Award

Patrick Ball won the Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society at the 2018 Joint Statistical Meeting.

Locating Hidden Graves in Mexico

For more than 10 years, and with regularity, Mexican authorities have been discovering mass graves, known as fosas clandestinas, in which hundreds of bodies and piles of bones have been found. The casualties are attributed broadly to the country’s “drug war,” although the motivations and perpetrators behind the mass murders are often unknown. Recently, HRDAG collaborated with two partners in Mexico—Data Cívica and Programa de Derechos Humanos of the Universidad Iberoamericana—to model the probability of identifying a hidden grave in each county (municipio). The model uses an set of independent variables and data about graves from 2013 ...

Coming soon: HRDAG 2019 Year-End Review

The online version of the 2019 Year-End Review will appear in January 2020.            

Our work has been used by truth commissions, international criminal tribunals, and non-governmental human rights organizations. We have worked with partners on projects on five continents.

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