Methods

I’ve Got the Power: A Survey of Issues Surrounding Statistical Power in the Design and Analysis of Survey Experiments

Clayton Webb (University of Kansas) and Cameron Wimpy (Arkansas State University)

Abstract: The power of a hypothesis test to reject a false null hypothesis is a basic concept of statistical inference that is introduced in most, if not all, introductory texts. Despite this, a systematic survey of work published in the American Journal of Political Science (AJPS), the American Political Science Review (APSR), the Journal of Politics (JOP...

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Ineffective Attribution Testing: An exploration of individual differences in cognition between Liberals and Conservatives

Stephanie Nail   (Stanford University)

Abstract: Previous literature has suggested that there are underlying differences in...

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Matching Estimation for Causal Effect on Compositional Outcomes

Kenichi Ariga   (University of Toronto)

Abstract: Compositional outcomes are not unusual in political science research....

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Framing Democracy: Identifying Autocratic Anti-Democratic Propaganda Using Word Embeddings

Patrick Chester (New York University)

Abstract: There is substantial empirical evidence that indicates that democracy can spread between countries through observational learning. But do autocracies try to bias learning against...

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Estimating Heterogeneous Effect on Clustered Data Using Mixed-Effects Model

Junlong Zhou (New York University)

Abstract: Estimating the heterogeneous treatment effect is essential to assess the generality and mechanism of randomized experiments. In this paper, we propose an extension of the regression forest combining mixed-effects to analyze heterogeneous treatment effect using aggregated data sets. We show that including mixed-effects can improve estimation by accounting for the cluster-level...

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Estimating Population Quantities From Multiple Data Sources Using the Structural Tensor Factorization

Soichiro Yamauchi (Harvard University)

Abstract: Estimating population quantities such as public opinions from survey data is a fundamental task in many social science studies. In political science, there is a growing interest in estimating public opinions at the level smaller than the entire nation, such as states (Lax and Phillips...

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Measuring Political Elite Networks With Wikidata

Omer Faruk Yalcin (Pennsylvania State University)

Abstract: An important issue in the study of comparative political elite networks is the elusiveness of cross-country empirical measurement. Most studies of political elites focus on country or region-specific institutions and use ad-hoc data collection methods like surveys...

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Gaussian Process Models for Causal Inference With Time-Series Cross-Sectional Data

Nuannuan Xiang and Kevin Quinn (University of Michigan)

*Award for Best Graduate Student Poster - Methods*

Abstract: In this paper, we develop a class of Gaussian Process models to estimate treatment effects with time-series cross-sectional data, in which a subset of units...

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Joint Image-Text Classification Using a Transformer-Based Architecture

Patrick Wu and Walter R. Mebane Jr. (University of Michigan)

Abstract: The use of social media data in political science is now commonplace. Social media posts such as Tweets are usually multimodal, comprising...

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Causal Inference Under Temporal and Spatial Interference

Ye Wang (New York University)

Abstract: Many social events and policies generate spillover effects in both time and space. Their occurrence influences not only the outcomes of interest in the future, but also these outcomes in nearby areas. In this paper, I propose a semi-parametric approach to estimate the direct and indirect/...

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Supervised Learning Election Forensics With Multi-Agent Simulated Training Data

Fabricio Vasselai (University of Michigan)

Abstract: The main advantage of using Supervised Machine Learning (SML) techniques to detect election fraud would be resorting to model-free or model-ensemble approaches, instead of usual...

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Rigorous Subjectivity: Demystifying and Improving Human Coding With Statistical Models

Matthew Tyler (Stanford University)

Abstract: Researchers are often tasked with applying subjective or contested labels to objects such as text and images. For example, researchers might hire coders to label the ideological slant of news articles. I show how two typical coding workflows in political science, traditional small-team...

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A Win or a Flop? Identifying and Estimating Unintended Protest Costs in Measuring Success Outcomes

Kimberly Turner (Southern Illinois University, Carbondale)

Abstract: How we measure protest success and how to identify and measure the lagged effects of movements has long besieged the field. Estimating the full impact of a movement, both its intended and unintended consequences, is undermined by the lack of consensus on...

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Multiplicative Interactions in Error Correction Models

Flávio Souza (Texas A&M University)

Abstract: Error correction modeling (ECM) is a common time-series strategy when both dependent and independent variables contain a unit root and are cointegrated. But one of its principal drawbacks is its inflexibility—since it requires that every independent variable enter the right-hand...

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Measuring Issue-Specific Preferences From Votes

Sooahn Shin (Harvard University)

Abstract: How can we measure issue-specific ideal points using roll-call votes? Ideal points have been widely used for measuring ideology, yet its nature of latent space makes it difficult to target a...

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