And in the spotlight, from Håvard Hungnes (Statistics Norway ) "A novel multivariate composite estimator for the Labour Force Survey" doi.org/10.1093/jrss...

🧵 April (and late March) highlights from JRSS-A! New original articles spanning networks, crime, genomics, finance & more. Thread 👇 (1/10)

There is now just one week left to get your talk on the programme for this September's @royalstatsoc.bsky.social conference in Bournemouth. Deadline for submissions 8 April. Don't miss out! rss.org.uk/training-eve...

Royal Statistical Society International Conference@rssannualconf.bsky.social · 6mo ago

Submissions for talks and posters are now open for @royalstatsoc.bsky.social 2026 International Conference. Deadline for contributed talk submissions is 8 April. #RSS2026Conf

💥 Bayesian spatiotemporal modelling of political violence and conflict events using discrete-time Hawkes processes Raiha Browning et al #ConflictData #Bayesian

👶 Learning Individual Reproductive Behavior from Aggregate Fertility Rates via Neural Posterior Estimation Ciganda et al. use neural posterior estimation to recover individual reproductive behaviour from fertility rates. #Demography #NeuralNetworks doi.org/10.1093/jrss...

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📣 Abstract submissions are open for #RSS2026! Join us and @rssannualconf.bsky.social in Bournemouth from 7–10 Sept, and share your work—whether it’s a 20‑min talk, a rapid‑fire session or a poster. Stats, data science, methodology, data storytelling… it’s all welcome! rss.org.uk/news-publica...

Submissions for talks open for RSS 2026 Conference

rss.org.uk

Hi everyone, sorry for being away for a while, we wanted to update you with the new papers! From mortality patterns to tax fraud detection, here's what's new 🧵👇"

📢 Call for Papers The Journal of the Royal Statistical Society, Series A (@jrssa.bsky.social) invites submissions for a special issue exploring historical data practices and their impact on modern data science. @royalstatsoc.bsky.social 🔍 Explore the full call: oxford.ly/4rgfcdl

🆕Bayesian evidence synthesis for modelling SARS-CoV-2 transmission 🧪Apsemidis and Demiris adopt the Bayesian paradigm and synthesize publicly available data via a discrete-time stochastic epidemic modelling framework doi.org/10.1093/jrss...

Bayesian evidence synthesis for modelling SARS-CoV-2 transmission

Abstract. The acute phase of the COVID-19 pandemic has made apparent the need for decision support based upon accurate epidemic modelling. This process is

doi.org

🆕A multilevel model with heterogeneous variances for snap timing in the National Football League 🏈Nguyen and Yurko snap into the passing lanes doi.org/10.1093/jrss...

A multilevel model with heterogeneous variances for snap timing in the National Football League

Abstract. Player tracking data have provided great opportunities to generate insights into understudied areas of American football, such as pre-snap motion

doi.org

🤔New tools for network time series with an application to COVID-19 hospitalisations Nason,Salnikov & Cortina-Borja present the following discussion paper (and you can find contributions to the discussion from other authors in the journal!) doi.org/10.1093/jrss...

Planning is underway for the 2026 International Conference which will take place in Bournemouth from 7-10 September. Submissions are now welcomed for invited topic sessions and workshops with a deadline of 21 November. Full details: rss.org.uk/training-eve...

Join Series A tomorrow for what promises to be a lively discussion meeting on Carl Morris' Finite Selection Model and its applications throughout experimental design

Journal of the Royal Statistical Society: Series A@jrssa.bsky.social · 10mo ago

We wanted to invite you to the next discussion paper meeting ‘Balanced and Robust Randomized Treatment Assignments: The Finite Selection Model for the Health Insurance Experiment and Beyond’ on October 22nd at 3 pm (UK time) (more details on link!) rss.org.uk/training-eve...

rss.org.uk/news-publication/news-publications/2025/member-callouts/associate-editors-sought-for-series-a/ We are looking for new editors for JRSSA! (details at the link) We are seeking associate editors for a four-year term starting in January 2026.

We wanted to invite you to the next discussion paper meeting ‘Balanced and Robust Randomized Treatment Assignments: The Finite Selection Model for the Health Insurance Experiment and Beyond’ on October 22nd at 3 pm (UK time) (more details on link!) rss.org.uk/training-eve...

🆕Latent class multi-state quantile regression with a cure fraction: application to jail recidivism in the USA 💡@barross993.bsky.social and @afarcome.bsky.social analyze time spent after release with a quantile regression approach doi.org/10.1093/jrss...

Latent class multi-state quantile regression with a cure fraction: application to jail recidivism in the U.S.

Abstract. We propose a multi-state quantile regression model that admits a cure-fraction for each possible transition, so that individuals may not experien

doi.org

🆕Improving survey inference in two-phase designs using Bayesian machine learning 🪶Wang, Chen, et al with a very clear purpose in the title of their paper doi.org/10.1093/jrss...

🆕Multilayer topology-aware graph contrastive learning for fraud detection in the Ethereum transaction network 💱Chen et al delve in Blockchain networks doi.org/10.1093/jrss...

Multilayer topology-aware graph contrastive learning for fraud detection in the Ethereum transaction network

Abstract. Fraud detection in blockchain networks presents unique challenges due to the decentralized and pseudonymous nature of transactions. This study in

doi.org

🆕A Bayesian approach to estimate causal peer influence accounting for latent network homophily 💡Um , Sweet and Adhikari show a framework to disentangle homophily from causal peer influence doi.org/10.1093/jrss...

🆕Bayesian analysis of diffusion-driven multi-type epidemic models with application to COVID-19 💡Bouranis et al. develop a flexible Bayesian evidence synthesis approach to model age-specific transmission dynamics of COVID-19 based on daily death counts

🆕Identifying enhanced generalized linear model estimation with nonignorable missing outcomes 💡Beppu, Choi, Morikawa & Im try to respond what happens when people don't respond to surveys because of their actual (unobserved) answer? doi.org/10.1093/jrss...

Identifying enhanced generalized linear model estimation with nonignorable missing outcomes

Abstract. Missing data often result in undesirable bias and loss of efficiency. These issues become substantial when the response mechanism is nonignorable

doi.org

🆕Robust inference for geographic regression discontinuity designs: assessing the impact of police precincts 💡Kendall et al analyze how smaller, sub-municipal boundaries like police districts, precincts, and service areas also influence police outcomes doi.org/10.1093/jrss...

Robust inference for geographic regression discontinuity designs: assessing the impact of police precincts

Abstract. We study variation in policing outcomes attributable to differential policing practices in New York City (NYC) using geographic regression discon

doi.org

Who increases emergency department (ED) use? New insights from the Oregon health insurance experiment 💡Austin Denteh and Helge Liebert estimate the heterogeneous impacts of Medicaid on ED use and characterize them doi.org/10.1093/jrss...

Who increases emergency department use? New insights from the Oregon health insurance experiment

Abstract. We provide new insights regarding the headline result that Medicaid increased emergency department (ED) use from the Oregon experiment. Using cau

doi.org

🆕Long-term trends of US county-level extreme ozone concentrations with long memory and changepoint considerations 🌬️Lee and Lee develop a long-memory extreme series model using a copula transformation to quantify long-term trends of extreme ozone doi.org/10.1093/jrss...

Long-term trends of US county-level extreme ozone concentrations with long memory and changepoint considerations

Abstract. We quantify long-term linear trends in weekly maximum ground-level ozone concentrations of 395 US counties by considering two critical issues: ch

doi.org

🆕Bayesian safe policy learning with chance constrained optimization: application to military security assessment during the Vietnam War 🤔Jia Ben-Michael and Imai examine whether a security assessment algorithm deployed during the Vietnam War could have been improved doi.org/10.1093/jrss...

Bayesian safe policy learning with chance constrained optimization: application to military security assessment during the Vietnam War

Abstract. Algorithmic decisions are increasingly used in high-stake domains such as criminal justice and medicine. We examine whether a security assessment

doi.org

🆕Counterfactual Q-learning via the linear Buckley–James method for longitudinal survival data ‼️Lee and Kim introduce the Counterfactual Buckley–James Q-Learning framework, to address challenges arising from longitudinal survival data. doi.org/10.1093/jrss...

Counterfactual Q-learning via the linear Buckley–James method for longitudinal survival data

Abstract. Treatment strategies are critical in healthcare, particularly when outcomes are subject to censoring. This study introduces the Counterfactual Bu

doi.org

🆕 Capturing the Spatio-Temporal Diffusion Effects of Armed Conflict: A Non-parametric Smoothing Approach 💡@dracek.bsky.social‬ Thurner and Kauermann develop a statistical model to capture the spatio-temporal diffusion effects of armed conflict (@lmumuenchen.bsky.social‬) doi.org/10.1093/jrss...

Capturing the spatio-temporal diffusion effects of armed conflict: A nonparametric smoothing approach

Abstract. Facilitated by advancements in conflict event databases, studies have moved towards predicting armed conflict and understanding its determinants

doi.org

🆕The effect of past successes on the probability of a current success: evidence from a natural experiment ♟️Adriaan Kalwij investigates the momentum effects to assess chess tournament performance doi.org/10.1093/jrss...

The effect of past successes on the probability of a current success: evidence from a natural experiment

Abstract. A theoretical prediction for performance in a tournament is that a player’s performance in a round can be affected by their results in previous r

doi.org

🆕A framework for studying causal effects of speech style: application to US presidential campaigns 💡Damann, Knox & Lucas develop a formal causal framework to overcome limitations of text-only analyses doi.org/10.1093/jrss...

A framework for studying causal effects of speech style: application to US presidential campaigns

Abstract. Numerous disciplines hypothesize about the causal effects of speech, which influences others not only through which words are spoken, but also ho

doi.org

🆕Spatially selected and dependent random effects for small area estimation with application to rent burden 💡Kawano Parker & Li we introduce a model that accounts for spatial dependence in random effects as well and effect selection latent processes doi.org/10.1093/jrss...