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Big Data, Selection Bias, and the Statistical Patterns of Mortality in Conflict

Megan Price and Patrick Ball (2014). SAIS Review of International Affairs © 2014 The Johns Hopkins University Press. This article first appeared in SAIS Review, Volume 34, Issue 1, Winter-Spring 2014, pages 9-20. All rights reserved.

Featured Video

Kristian Lum, lead statistician at HRDAG | Predictive Policing: Bias In, Bias Out | 56 mins

How much faith can we place in coronavirus antibody tests?

Given a positive test result, what is the probability that an individual has antibodies? This HRDAG-authored Granta article explains the science.

Overbooking’s Impact on Pre-Trial Risk Assessment Tools

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

Podcast: Dr. Patrick Ball on Using Statistics to Uncover Truth

Dr. Patrick Ball recently visited the Plutopia News Network podcast for a wide-ranging, inspiring conversation about his work for the Human Rights Data Analysis Group. Patrick spoke about how he first discovered human rights work during his time in El Salvador with the Peace Brigades International.  That led to his ongoing work as a statistician and computer programmer working to assess and analyze human rights violations. He also unpacked some common statistical techniques used by researchers at Human Rights Data Analysis Group, such as multiple systems estimation, which uses multiple different datasets to gain insights into the data we don't ...

Multiple Systems Estimation: Collection, Cleaning and Canonicalization of Data

<< Previous post: MSE: The Basics Q3. What are the steps in an MSE analysis? Q4. What does data collection look like in the human rights context? What kind of data do you collect? Q5. [In depth] Do you include unnamed or anonymous victims in the matching process? Q6. What do you mean by "cleaning" and "canonicalization?" Q7. [In depth] What are some of the challenges of canonicalization? (more…)

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.

Uncertainty in COVID Fatality Rates

In this Granta article, HRDAG explains that neither the infectiousness nor the deadliness of the disease is set in stone.

Welcoming Our New Statistician

Maria Gargiulo has joined HRDAG as a Statistician.

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 ...

HRDAG Names New Board Member Margot Gerritsen

Margot is a professor in the Department of Energy Resources Engineering at Stanford University, interested in computer simulation and mathematical analysis of engineering processes.

Partners

How we work with partners is how we relate to the whole human rights community. We work with human rights advocates and defenders to support their goals by complementing their substantive expertise with our technical expertise. To date, partners have included truth commissions, international criminal tribunals, United Nations missions, and non-governmental human rights organizations on five continents. Here are a few stories that illustrate how we work with our partners: HRDAG partner stories: Quantifying Police Misconduct in Louisiana (2023) Scraping for Pattern: Protecting Immigrant Rights in Washington State (2022) Police Violence ...

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.

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

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.

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.

Setting the Record Straight on Predictive Policing and Race

William Isaac and Kristian Lum (2018). Setting the Record Straight on Predictive Policing and Race. In Justice Today. 3 January 2018. © 2018 In Justice Today / Medium.

William Isaac and Kristian Lum (2018). Setting the Record Straight on Predictive Policing and Race. In Justice Today. 3 January 2018. © 2018 In Justice Today / Medium.

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.

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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