Official Journal of the Society for Political Methodology
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We're back! We are excited to share lots of new and exciting research with you all here and on our new Bluesky account. Find us at polanalysis.bsky.social!
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Currently in FirstView: In “Let Them Eat Pie: Addressing Sample Selection in Multiparty Elections,” Ali Kagalwala, Thiago Moreira, Guy Whitten, and Yongzhi Xu introduce a maximum likelihood approach that accounts for sample selection biases in a compositional setting.
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They show that partial contestation constitutes a form of sample selection and illustrate their approach by analyzing the 2017 and 2019 U.K. parliamentary elections. Read the full paper here: cambridge.org/core/journals/…
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Currently in FirstView: In “The Power of Prognosis: Improving Covariate Balance Tests with Outcome Information,” @clara_bmc, @AdamBouyamourn, and @thaddunning show how balance tests can lead to false conclusions and develop tests that upweight covariates associated with outcomes.
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They adapt their approach for regression-discontinuity designs and show how prognosis weighting can avoid both false negatives and false positives. Read the full paper here: cambridge.org/core/journals/…
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Currently in FirstView: In “Monotone Ecological Inference,” @hselzayn, @jacobsgoldin, Cameron Guage, Daniel Ho, and Claire Morton characterize the biases of, and relationships among ecological inference (EI) estimators for identifying group means and differences.
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The authors develop a partial identification approach, monotone EI, and illustrate it using county-level data on partisanship and COVID-19 vaccines. You can read the paper here: cambridge.org/core/journals/…
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Currently in FirstView: In “On the Foundations of the Design-Based Approach,” P. M. Aronow, Austin Jang, and @mofferw propose a design-based framework for analyzing randomized trials and survey sampling that avoids strong claims about the data-generating process.
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The authors provide two stylized examples illustrating this framework, establish key elements of the analysis, and discuss the interpretation of results under STUVA as well as a weaker assumption (NURVA). Read the full paper here: cambridge.org/core/journals/…
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Currently in FirstView: In “Post-Treatment Problems: What Can We Say about the Effect of a Treatment among Sub-Groups Who (Would) Respond in Some Way?,” @chadhazlett, Nina McMurry, and @TanviShinkre propose the treatment reactive average causal effect (TRACE).
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TRACE is the total effect of treatment in the group that would realize a particular value of the relevant post-treatment variable. Unlike other approaches, TRACE does not require strong and untestable assumptions. Read the paper here: cambridge.org/core/journals/…
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Currently in FirstView: In “Estimating Treatment Effects on Proportions with Synthetic Controls,” @konboga and Lukas Stoetzer examine synthetic control methods (SCMs) and make the case for jointly estimating synthetic controls across multiple compositional outcomes.
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Using a simulation and two replication studies, they demonstrate that this approach adheres to the compositional data constraints and offers a more accurate interpretation of estimated treatment effects for proportional outcomes. Read the paper here: cambridge.org/core/journals/…
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Currently in FirstView: In “Improving Small-Area Estimates of Public Opinion by Calibrating to Known Population Quantities,” @wpmarble and @joshclinton provide a framework for incorporating known population data to improve estimates of small subgroups in MRP models.
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They validate this method using pre-election polling from the 2022 Michigan midterm and find that their calibrated MRP estimates reduce error by as much as two thirds. You can read the full paper here: cambridge.org/core/journals/…
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Currently in FirstView: In “Text as Behavior,” @owasow proposes using features of open-ended tasks to study text as behavior. Stats like the number of characters can approximate effort and significantly improve estimation.
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The paper walks through three studies where text is used to quantify attitudes and actions. Ultimately, the paper argues that expression is sufficiently demanding that it should be understood as a form of action. Read the paper here: cambridge.org/core/journals/…
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Currently in FirstView: In “Democracy Manifest or Democracy Latent? A Unified Framework for Identifying Regime Types and Transitions,” @OmerFOrsun and @muhammet_a_bas develop and validate a framework to study regimes that addresses measurement uncertainty and missing data.
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Their framework, UNITAS, reduces the dependence of inferences on specific datasets, cut-offs, magnitude-of-change and time-window assumptions, while efficiently handling missingness and measurement uncertainty. You can read the paper here: cambridge.org/core/journals/…
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Currently in FirstView: In “Using Multilingual Language Technology to Classify Open-Ended Survey Responses: Conceptions of Democracy in a Cross-Cultural Survey Setting,” @StefanDahlberg, @JoakimNivre, and coauthors examine the use of LMs in analyzing survey open-ended responses.
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The authors introduce a methodology that integrates LMs and structured coding schemes to classify open-ended survey responses cost-effectively and find that LMs can capture democratic perceptions and handle data abstractions. Read the full paper here: cambridge.org/core/journals/…
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