2020 Best Poster Awards

After a careful perusal of a very competitive field of 83 posters, the prize committee is pleased to announce the following three awards.

Best graduate student methods poster: shared by Melody Huang (UCLA) and Nuannuan Xiang (Michigan)

Huang's poster, "Leveraging Observational Outcomes To Improve the Generalization Of Experimental Results", takes an innovative approach that leverages outcome data in the target population to improve the precision of the population estimate by residualizing the sample data before doing inverse propensity weighting. Melody goes on to reanylze a multi-site experiment and finds her method delivers more precise estimates of a known experimental benchmark.

Xiang's poster entitled "A Gaussian Process Model for Causal Inference with TSCS Data" compares her GP model with the state of the art GSC model. The GP approach mostly returns tighter credible intervals, though it does not track the March 2020 shock to unemployment. We expect that the paper iteration of this paper will provide more guidance on what aspect of the model's nonlinearity leads to its impressive ability to outperform the GSC.

Best graduate student applied poster: shared by Erin Rossiter (WashU) and Luwei Ying (WashU)

Rossiter's poster, "The Consequences of Interparty Conversation on Outparty Affect and Stereotypes", examined why Americans increasingly dislike members of the opposite political party, a vital issue as our democracy strains due to increasing polarization. Erin combines two important innovations. First, she implements a blocked cluster design that facilitates statistically efficient analysis of experimental treatments. Second, she develops a chat software that allows people to have real-time written conversations on-line. This design allows her to analyze the effects of different types of interactions. While those with no contact with members of the other political party exhibit no change in their feelings toward the other party, those who engage in a conversation exhibit clearly warmer feelings toward members of the other party. The effects appear roughly similar for both political and non-political conversations. These results provide new evidence that interparty social interaction, regardless of whether the conversation is politically-charged or not, can work to undo the negative view of outparty members held by many Americans.

Ying's Poster entitled "Religiosity and Secularism: A Text-as-Data Approach to Recover Jihadist Groups’ Rhetorical Strategies" tests the hypothesis that as Jihadist groups become stronger their rhetoric moves along a continuum from religious to secular, while it moves back again when events turn against the Jihadis. To operationalize this Luwei gathered an impressive multilingual corpus spanning decades of Jihadi literature, and hand coded it, with separate filters for religious and secular vocabulary in each language. Ying shows that the log odds of using secular vocabulary does indeed rise and fall with variables measuring the political success of the Jihadis. Luwei goes on to provide confirmatory analysis using twitter.

Best faculty poster: Jay Goodliffe (BYU)

For his poster "Using Latent Transition Analysis to Explain Donor Behavior", in which he analyzes why citizens start and stop donating to campaigns. This is an important question because most donors give only occasional small amounts. Jay develops a sophisticated latent transition model to identify patterns of giving. One pattern, for example, is donors who give only to presidential candidates, while another pattern is a donor who contributes medium-size donations to out-of-state congressional candidates. Jay’s approach allows him to analyze transitions from one pattern to another finding, for example, that donating in a presidential election does not generally lead people to become donors in midterms. Goodliffe’s work combines rigorous statistical techniques with informative visualizations to help us better understand an important political phenomenon.

We thank the authors of all 83 of the posters in this extremely strong field for the opportunity to learn about their work!