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THE COMPUTATIONAL SOCIAL SCIENCE WORKSHOP PRESENTS</h3>
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GUANGLEI HONG</h1>
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ASSOCIATE PROFESSOR IN THE DEPARTMENT OF COMPARATIVE HUMAN DEVELOPMENT</h3>
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UNIVERSITY OF CHICAGO</h3>
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The <a href="https://macss.uchicago.edu/content/computation-workshop" style="box-sizing: border-box; color: rgb(66, 139, 202); text-decoration: none; transition: all 0.125s ease-in-out 0s;">Computational Social Science Workshop </a>at the University of Chicago
cordially invites you to attend this week’s talk:</p>
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<a href="https://github.com/uchicago-computation-workshop/guanglei_hong/blob/master/2017__hong__ratio_of_mediator_probability_weighting.pdf" style="box-sizing: border-box; color: rgb(66, 139, 202); text-decoration: none; transition: all 0.125s ease-in-out 0s;">UNPACKING
BETWEEN-SITE HETEROGENEITY IN COMPLEX CAUSAL MECHANISMS: THE NATIONAL JOB CORPS STUDY</a></h2>
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<span style="box-sizing: border-box; font-weight: 700;">Abstract:</span> Causal mediation analysis in a multisite study is particularly intriguing because the researcher may not only test the program theory about intermediate mechanisms but also investigate
whether these mechanisms operate differently across different contexts. In a series of studies, our research team re-analyzes the National Job Corps study, investigating whether Job Corps—the nation’s largest job training program for disadvantage youth—improved
economic well-being through human capital formation, whether general education and vocational training were complementary or mutually reinforcing, and whether a wide array of supplementary services offered by Job Corps also contributed to the program impact.
We develop new concepts and novel analytic strategies to overcome multiple methodological challenges in defining, identifying, and estimating the causal parameters and in sensitivity analysis.</p>
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THURSDAY, 11/16/2017</h4>
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11:00AM-12:20PM</h4>
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KENT 120</h4>
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A light lunch will be provided by Good Earth Catering Company.</p>
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<span style="box-sizing: border-box; font-weight: 700;">Dr. Guanglei Hong</span> is Associate Professor with tenure in the Comparative Human Development Department and the Committee on Education at the University of Chicago. She is an active member of the quantitative
methodology community at the University. She obtained a Master’s degree in Statistics in 2002 and a Ph.D. in Education in 2004 from the University of Michigan.</p>
<span style="color: rgb(102, 102, 102); font-family: Raleway, sans-serif; font-size: 14px; background-color: rgb(255, 255, 255);">Dr. Hong develops and applies causal inference theories and methods for evaluating educational and social policies and programs
in multi-level, longitudinal settings. Her work is currently focused on developing concepts and methods for analyzing causal mediation mechanisms in multisite randomized trials. She has received research funding from the National Science Foundation (NSF),
the Institute of Education Sciences (IES) of the U.S. Department of Education, the William T Grant Foundation, the Spencer Foundation, and the Social Sciences and Humanities Research Council (SSHRC) of Canada.</span>
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The 2017-2018 <a href="https://macss.uchicago.edu/content/computation-workshop" style="box-sizing: border-box; color: rgb(66, 139, 202); text-decoration: none; transition: all 0.125s ease-in-out 0s;">Computational Social Science Workshop </a>meets each Thursday
from 11 to 12:20 p.m. in Kent 120. All interested faculty and graduate students are welcome.</p>
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Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the <a href="https://github.com/uchicago-computation-workshop/guanglei_hong/issues" style="box-sizing: border-box; color: rgb(66, 139, 202); text-decoration: none; transition: all 0.125s ease-in-out 0s;">issues
page </a>of the <a href="https://github.com/uchicago-computation-workshop/guanglei_hong" style="box-sizing: border-box; color: rgb(66, 139, 202); text-decoration: none; transition: all 0.125s ease-in-out 0s;">workshop’s public repository on GitHub.</a> Further
instructions are documented in the Computational Social Science Workshop’s <a href="https://github.com/uchicago-computation-workshop/README" style="box-sizing: border-box; color: rgb(66, 139, 202); text-decoration: none; transition: all 0.125s ease-in-out 0s;">README
on Github.</a></p>
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