Presentations

9/26 - Shihao Yang presents "Big data, Google, and infectious disease prediction: a statistical perspective", at 12-1:30 pm - K354 - CGIS Knafel Building, Wednesday, September 26, 2018

Abstract: Big data generated from the internet have great potential in tracking and predicting massive social activities, in particular infectious diseases, whose accurate real-time prediction could help public health officials make timely decisions to save lives. We introduce a model ARGO (AutoRegression with GOogle search data / AutoRegression with General Online data) that has successfully utilized publicly available Google search data, with/without cloud-based electronic health records, to estimate current and near-future influenza-like illness...

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9/19/2018 - Aaron Kaufman presents "An Automated Method to Estimate Survey Question Bias" , at K354 - CGIS Knafel Building, Wednesday, September 19, 2018:

Abstract: Many survey researchers are interested in gauging public support for government policy, but there is strong evidence that a question’s wording affects responses to it. I develop the first automated and scalable method to predict the magnitude and direction of the partisan bias a question’s wording may impose on survey responses, and show using a series of survey experiments that it outperforms public opinion scholars in predicting that bias. Using a novel data set of almost one million survey questions from 1997 to 2017, I then examine trends in...

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9/12/2018 - Junming Huang presents "Quantifying Gender Inequality in Scientific Careers" , at 12-1:30 pm - K354 - CGIS Knafel Building, Wednesday, September 12, 2018
Abstract: Gender inequality in academic careers, documented across all disciplines and countries, extends beyond the fraction of women involved in research: compared to their male colleagues, women publish less over the course of their careers and their work acquires fewer citations. Yet, all existing evidence is limited to selected countries or disciplines, restricting our ability assess the roots and implications of the gender disparity. Here we analyzed a large corpus of scientific publications since 1900, identifying the gender and reconstructing the full publishing career...
Read more about 9/12/2018 - Junming Huang presents "Quantifying Gender Inequality in Scientific Careers"
4/25/18 - Jeff Gill presents "Models for Identifying Substantive Clusters and Fitted Subclusters in Social Science Data", at CGIS Knafel K354, Wednesday, April 25, 2018

Jeff Gill presents

 

Models for Identifying Substantive Clusters and Fitted Subclusters in Social Science Data

Unseen grouping, often called latent clustering, is a common feature in social science data.  Subjects may intentionally or unintentionially group themselves in ways that complicate the statistical analysis of substantively important relationships. This work introduces a new model-based clustering design which incorporates two sources of heterogeneity.  The first source is a random effect that introduces substantively unimportant...

Read more about 4/25/18 - Jeff Gill presents "Models for Identifying Substantive Clusters and Fitted Subclusters in Social Science Data"
4/18/18- Xiang Zhou presents "Two residual-based methods to adjust for treatment-induced confounding in causal inference", at CGIS Knafel K354, Wednesday, April 18, 2018

Xiang Zhou presents "Two residual-based methods to adjust for treatment-induced confounding in causal inference"

 

Two residual-based methods to adjust for treatment-induced confounding in causal inference 

 

Treatment-induced confounding arises in both causal inference of time-varying treatments and causal mediation analysis where post-treatment variables affect both the mediator and outcome. Existing methods to adjust for treatment-induced confounding include, among others, Robins's structural nest mean model (SNMM) with its g-... Read more about 4/18/18- Xiang Zhou presents "Two residual-based methods to adjust for treatment-induced confounding in causal inference"
4/11/18 - Michael Windzio presents "Does schoolwork cooperation improve pupils’ grades and well-being in school? Results from social network and propensity score analysis", at CGIS Knafel K354, Wednesday, April 11, 2018


Does schoolwork cooperation improve pupils’ grades and well-being in school? Results from social network and propensity score analysis


Using panel data of school-class networks and outcomes of 11-13-year-old students, effects of collaboration in schoolwork networks on grades and school-related well-being will be investigated. The analysis might suffer from endogeneity-bias because pupils actively select their peers also with regard to their school-performance. This selectivity will be demonstrated by using p* models for ties in schoolwork-networks at t1 based data of 1,289...

Read more about 4/11/18 - Michael Windzio presents "Does schoolwork cooperation improve pupils’ grades and well-being in school? Results from social network and propensity score analysis"
3/28/18 - Michelle Torres Pacheco presents "Understanding visual messages: visual framing and the Bag of Visual Words", at CGIS Knafel K354, Wednesday, March 28, 2018

Michelle Torres Pacheco presents. 

 

TITLE: Understanding visual messages: visual framing and the Bag of Visual Words

ABSTRACT
Political communication is a central element of several political dynamics. Its visual component is crucial in understanding the origin, characteristics and consequences of the messages sent between political figures, media and citizens. However, visual features have been largely overlooked in Political Science. In this project, I implement computer vision and image retrieval techniques to measure and understand messages...

Read more about 3/28/18 - Michelle Torres Pacheco presents "Understanding visual messages: visual framing and the Bag of Visual Words"

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