Official Journal of the Society for Political Methodology

Joined September 2010
The October 2026 issue of Political Analysis (Volume 34, Issue 4) is out, and every article is open access. Eight papers on protest voting, coalition governments, conjoint designs, Gaussian processes, vision-language models, and more. Highlights below 🧵 cambridge.org/core/journals/…
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New on FirstView: which cases drive a regression result? Melamed, Wippell, Schoon & Breiger extend Regression Inside Out to hazard models and beyond. Re-analyzing a democracy study, they find South Africa contributes disproportionately to the key effect. doi.org/10.1017/pan.2026.100…
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New on FirstView: in two field experiments with a Dutch party’s 35,000+ members, Jonne Kamphorst & Horacio Larreguy find personal calls raised volunteer sign-ups (+83% and +361%, from low baselines), especially among younger members. Emails had no effect. doi.org/10.1017/pan.2026.100…
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New on FirstView: weighting can fail when nonrespondents differ on the outcome. Lafférs, Mintal & Sutóris extend a fix to ordinal scales. In the 2024 ANES, it shifts life satisfaction meaningfully but economic views only modestly. doi.org/10.1017/pan.2026.100…
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Letter: Jonathan Colner shows how free computer vision tools can extract text sections from poorly formatted PDFs. Pulling agenda items from council minutes took about an hour per city vs. ~31 hours by hand, and closely matched two ground-truth datasets. doi.org/10.1017/pan.2025.100…
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Letter: Do AI models read ideology from faces? Jeon, Lee, Montgomery & Lai varied only the face in neutral campaign ads. All three models rated women more liberal than men, beyond survey gaps. Racial effects varied by model. doi.org/10.1017/pan.2026.100…
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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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