Journal of the Royal Statistical Society: Series A
@jrssa.bsky.social
JRSS-A publishes research showing how statistics play a vital role in life and benefit society l #data l #statistics | #academic | #bayesian | #stochastic
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academic.oup.com/jrsssa
Reposted by Journal of the Royal Statistical Society: Series A
📢 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
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
November 20, 2025 at 6:00 PM
📢 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
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...
🧪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
November 21, 2025 at 2:18 PM
🆕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...
🧪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...
🆕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...
🏈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
November 21, 2025 at 2:17 PM
🆕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...
🏈Nguyen and Yurko snap into the passing lanes
doi.org/10.1093/jrss...
🤔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...
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...
Validate User
doi.org
November 14, 2025 at 1:14 PM
🤔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...
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...
Submissions are now welcomed for invited topic sessions and workshops with a deadline of 21 November. Full details: rss.org.uk/training-eve...
Invited topic sessions
rss.org.uk
November 14, 2025 at 1:13 PM
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...
Submissions are now welcomed for invited topic sessions and workshops with a deadline of 21 November. Full details: rss.org.uk/training-eve...
Reposted by Journal of the Royal Statistical Society: Series A
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
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/training-eve...
Discussion paper meetings
rss.org.uk
October 21, 2025 at 9:52 AM
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
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 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.
Associate editors sought for Series A
rss.org.uk
October 22, 2025 at 9:25 AM
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 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...
rss.org.uk/training-eve...
Discussion paper meetings
rss.org.uk
October 20, 2025 at 7:44 PM
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/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...
💡@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
October 3, 2025 at 1:00 PM
🆕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...
💡@barross993.bsky.social and
@afarcome.bsky.social
analyze time spent after release with a quantile regression approach
doi.org/10.1093/jrss...
🆕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...
🪶Wang, Chen, et al with a very clear purpose in the title of their paper
doi.org/10.1093/jrss...
Validate User
doi.org
October 3, 2025 at 12:51 PM
🆕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...
🪶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...
💱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
October 1, 2025 at 2:53 PM
🆕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...
💱Chen et al delve in Blockchain networks
doi.org/10.1093/jrss...
🆕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...
💡Um , Sweet and Adhikari show a framework to disentangle homophily from causal peer influence
doi.org/10.1093/jrss...
Validate User
doi.org
September 23, 2025 at 9:02 AM
🆕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...
💡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
💡Bouranis et al. develop a flexible Bayesian evidence synthesis approach to model age-specific transmission dynamics of COVID-19 based on daily death counts
September 19, 2025 at 8:12 AM
🆕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
💡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...
💡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
September 19, 2025 at 8:10 AM
🆕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...
💡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...
🆕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...
💡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
September 3, 2025 at 12:01 PM
🆕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...
💡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...
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...
💡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
August 26, 2025 at 12:28 PM
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...
💡Austin Denteh and Helge Liebert
estimate the heterogeneous impacts of Medicaid on ED use and characterize them
doi.org/10.1093/jrss...
🆕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...
🌬️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
August 21, 2025 at 9:18 AM
🆕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...
🌬️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...
🆕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...
🤔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
August 21, 2025 at 9:16 AM
🆕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...
🤔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...
🆕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...
‼️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
August 12, 2025 at 12:44 PM
🆕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...
‼️Lee and Kim introduce the Counterfactual Buckley–James Q-Learning framework, to address challenges arising from longitudinal survival data.
doi.org/10.1093/jrss...
🆕 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...
💡@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
August 6, 2025 at 3:13 PM
🆕 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...
💡@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...
🆕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...
♟️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
July 22, 2025 at 6:04 PM
🆕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...
♟️Adriaan Kalwij investigates the momentum effects to assess chess tournament performance
doi.org/10.1093/jrss...
🆕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...
💡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
July 22, 2025 at 6:02 PM
🆕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...
💡Damann, Knox & Lucas develop a formal causal framework to overcome limitations of text-only analyses
doi.org/10.1093/jrss...
🆕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...
💡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...
July 22, 2025 at 6:00 PM
🆕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...
💡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...
🆕Flexible Bayesian modelling of age-specific counts in many demographic subpopulations
💡Zens proposes a Bayesian model for the joint analysis of age-specific counts in many, potentially small, demographic subpopulations
doi.org/10.1093/jrss...
💡Zens proposes a Bayesian model for the joint analysis of age-specific counts in many, potentially small, demographic subpopulations
doi.org/10.1093/jrss...
Flexible Bayesian modelling of age-specific counts in many demographic subpopulations
Abstract. Analysing age-specific mortality, fertility, and migration patterns is a crucial task in demography with significant policy relevance. In practic
doi.org
June 30, 2025 at 12:16 PM
🆕Flexible Bayesian modelling of age-specific counts in many demographic subpopulations
💡Zens proposes a Bayesian model for the joint analysis of age-specific counts in many, potentially small, demographic subpopulations
doi.org/10.1093/jrss...
💡Zens proposes a Bayesian model for the joint analysis of age-specific counts in many, potentially small, demographic subpopulations
doi.org/10.1093/jrss...
🆕Estimating methane emissions from the upstream oil and gas industry using a multi-stage framework
💡Wigle and Béliveau provide a method for estimating methane inventories that are simple to interpret
t.co/wWXhJhmTGq
💡Wigle and Béliveau provide a method for estimating methane inventories that are simple to interpret
t.co/wWXhJhmTGq
https://doi.org/10.1093/jrsssa/qnaf060
t.co
June 30, 2025 at 12:14 PM
🆕Estimating methane emissions from the upstream oil and gas industry using a multi-stage framework
💡Wigle and Béliveau provide a method for estimating methane inventories that are simple to interpret
t.co/wWXhJhmTGq
💡Wigle and Béliveau provide a method for estimating methane inventories that are simple to interpret
t.co/wWXhJhmTGq