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NISS Ingram Olkin Forum: Statistical Methods for Combatting Human Trafficking
This webinar has expert speakers who will describe statistical approaches for estimating prevalence, especially multiple systems estimation, respondent-driven sampling, and economic modeling. The pros and cons of these methods will be discussed. This is a three-hour webinar with two 15-minute break. Each speaker will have 30 minutes, with a final 30 minutes for discussion.

Speakers for this IOF include Margaret Henderson, (University of North Carolina); Nancy E. Hagan (North Carolina Human Trafficking Commission); Tyler McCormick, (University of Washington); and Bernard Silverman, (Oxford University). Our Forum Chair will be David Banks, (Duke University).

NISS event page: https://www.niss.org/events/ingram-olkin-forum-statistical-methods-combatting-human-trafficking

Mar 15, 2023 01:00 PM in Eastern Time (US and Canada)

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Speakers

Margaret Henderson
@University of North Carolina
Margaret Henderson is a Teaching Associate Professor with the School of Government at the University of North Carolina at Chapel Hill. Her current work primarily includes training professionals engaged in public service, facilitating public meetings and assisting local governments to address human trafficking and elder abuse. In facilitation work, she specializes in the practical implications of managing cross-organizational collaborations.
Nancy Hagan
@North Carolina Human Trafficking Commission
Nancy Hagan, PhD, is the Senior Human Trafficking Analyst for Project NO REST whose expertise includes coalition building and direct service with LEP Spanish-speaking individuals and community groups, in particular immigrants and farmworkers, around issues of labor and sex trafficking.
Tyler McCormick
@University of Washington
Tyler McCormick is an Associate Professor in the Statistics and Sociology Department at University of Washington. His research has been devoted to two themes: how to develop statistical methods to learn about social network structure using sampled or partially observed network data; and how to leverage social structure in social networks to access populations that are excluded from the sampling frame of most surveys (the homeless, or individuals living with HIV, for example). McCormick’s work on statistical methods have focused primarily on “How many X’s do you know?’’ data. He has published papers on estimating respondents’ degrees, the population degree distribution, and levels of overdispersion (excess variation in the data due to social structure). McCormick’s most recent work in this area is a new class of statistical models based on latent space models proposed in the complete network literature.
Bernard Silverman
@Oxford University
Sir Bernard Silverman is a statistician whose research has ranged widely across theoretical and practical aspects of statistics. He is recognized as a pioneer of computational statistics, researching the ways that computing power has changed our ability to collect, analyse, understand and utilise data. He has published extensively in this field, covering aspects from the fundamental mathematical properties of new methods to computer packages for their implementation. He has collaborated in many fields in the physical, life and social sciences, and with various areas of industry and government.
Rowland Seymour
@University of Birmingham
Rowland Seymour is Assistant Professor of Mathematics in the University of Birmingham. His research interests are in computational statistics and Bayesian nonparametrics. Rowland has developed models for a wide range of applications including human rights abuses and outbreaks of infectious diseases. Before taking up his current role, he was a Senior Research Fellow at the University of Nottingham’s Rights Lab, where he led the Prevalence and Computation group.