Scholars@Duke
Alexander Volfovsky

Alexander Volfovsky

Associate Professor of Statistical Science
Statistical Science
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Selected Publications

Stochastic EM algorithm for partially observed stochastic epidemics with individual heterogeneity.

Journal Article Biostatistics (Oxford, England) · August 2024 We develop a stochastic epidemic model progressing over dynamic networks, where infection rates are heterogeneous and may vary with individual-level covariates. The joint dynamics are modeled as a continuous-time Markov chain such that disease transmission ... Full text Cite

Bias and excess variance in election polling: a not-so-hidden Markov model

Journal Article Journal of the Royal Statistical Society Series A: Statistics in Society · July 25, 2024 AbstractWith historic misses in the 2016 and 2020 US Presidential elections, interest in measuring polling errors has increased. The most common method for measuring directional errors and non-sampling exces ... Full text Cite

How many patients do you need? Investigating trial designs for anti-seizure treatment in acute brain injury patients.

Journal Article Annals of clinical and translational neurology · July 2024 Background/objectivesEpileptiform activity (EA), including seizures and periodic patterns, worsens outcomes in patients with acute brain injuries (e.g., aneurysmal subarachnoid hemorrhage [aSAH]). Randomized control trials (RCTs) assessing anti-se ... Full text Cite

Reducing political polarization in the United States with a mobile chat platform.

Journal Article Nature human behaviour · September 2023 Do anonymous online conversations between people with different political views exacerbate or mitigate partisan polarization? We created a mobile chat platform to study the impact of such discussions. Our study recruited Republicans and Democrats in the Un ... Full text Cite

Likelihood-Based Inference for Partially Observed Epidemics on Dynamic Networks

Journal Article Journal of the American Statistical Association · January 1, 2022 We propose a generative model and an inference scheme for epidemic processes on dynamic, adaptive contact networks. Network evolution is formulated as a link-Markovian process, which is then coupled to an individual-level stochastic susceptible-infectious- ... Full text Cite

Reinforcement Learning Methods in Public Health.

Journal Article Clinical therapeutics · January 2022 PurposeReinforcement learning (RL) is the subfield of machine learning focused on optimal sequential decision making under uncertainty. An optimal RL strategy maximizes cumulative utility by experimenting only if and when the information generated ... Full text Cite

Assortativity and Bias in Epidemiologic Studies of Contagious Outcomes: A Simulated Example in the Context of Vaccination.

Journal Article American journal of epidemiology · November 2021 Assortativity is the tendency of individuals connected in a network to share traits and behaviors. Through simulations, we demonstrated the potential for bias resulting from assortativity by vaccination, where vaccinated individuals are more likely to be c ... Full text Cite

Multiple Imputation Using Gaussian Copulas

Journal Article Sociological Methods and Research · August 1, 2021 Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this article, we present a si ... Full text Cite

Author Clustering and Topic Estimation for Short Texts

Journal Article · June 15, 2021 Analysis of short text, such as social media posts, is extremely difficult because of their inherent brevity. In addition to classifying topics of such posts, a common downstream task is grouping the authors of these documents for subsequent analyses. We p ... Link to item Cite

SARS-CoV-2 Infection in Health Care Personnel and Their Household Contacts at a Tertiary Academic Medical Center: Protocol for a Longitudinal Cohort Study.

Journal Article JMIR research protocols · April 2021 BackgroundHealth care personnel (HCP) are at high risk for exposure to the SARS-CoV-2 virus. While personal protective equipment (PPE) may mitigate this risk, prospective data collection on its use and other risk factors for seroconversion in this ... Full text Cite

dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference

Journal Article · January 5, 2021 dame-flame is a Python package for performing matching for observational causal inference on datasets containing discrete covariates. This package implements the Dynamic Almost Matching Exactly (DAME) and Fast Large-Scale Almost Matching Exactly (FLAME) al ... Open Access Link to item Cite

FLAME: A fast large-scale almost matching exactly approach to causal inference

Journal Article Journal of Machine Learning Research · January 1, 2021 A classical problem in causal inference is that of matching, where treatment units need to be matched to control units based on covariate information. In this work, we propose a method that computes high quality almost-exact matches for high-dimensional ca ... Open Access Cite

Stochastic EM algorithm for partially observed stochastic epidemics with individual heterogeneity.

Journal Article Biostatistics (Oxford, England) · August 2024 We develop a stochastic epidemic model progressing over dynamic networks, where infection rates are heterogeneous and may vary with individual-level covariates. The joint dynamics are modeled as a continuous-time Markov chain such that disease transmission ... Full text Cite

Bias and excess variance in election polling: a not-so-hidden Markov model

Journal Article Journal of the Royal Statistical Society Series A: Statistics in Society · July 25, 2024 AbstractWith historic misses in the 2016 and 2020 US Presidential elections, interest in measuring polling errors has increased. The most common method for measuring directional errors and non-sampling exces ... Full text Cite

How many patients do you need? Investigating trial designs for anti-seizure treatment in acute brain injury patients.

Journal Article Annals of clinical and translational neurology · July 2024 Background/objectivesEpileptiform activity (EA), including seizures and periodic patterns, worsens outcomes in patients with acute brain injuries (e.g., aneurysmal subarachnoid hemorrhage [aSAH]). Randomized control trials (RCTs) assessing anti-se ... Full text Cite

Reducing political polarization in the United States with a mobile chat platform.

Journal Article Nature human behaviour · September 2023 Do anonymous online conversations between people with different political views exacerbate or mitigate partisan polarization? We created a mobile chat platform to study the impact of such discussions. Our study recruited Republicans and Democrats in the Un ... Full text Cite

Likelihood-Based Inference for Partially Observed Epidemics on Dynamic Networks

Journal Article Journal of the American Statistical Association · January 1, 2022 We propose a generative model and an inference scheme for epidemic processes on dynamic, adaptive contact networks. Network evolution is formulated as a link-Markovian process, which is then coupled to an individual-level stochastic susceptible-infectious- ... Full text Cite

Reinforcement Learning Methods in Public Health.

Journal Article Clinical therapeutics · January 2022 PurposeReinforcement learning (RL) is the subfield of machine learning focused on optimal sequential decision making under uncertainty. An optimal RL strategy maximizes cumulative utility by experimenting only if and when the information generated ... Full text Cite

Assortativity and Bias in Epidemiologic Studies of Contagious Outcomes: A Simulated Example in the Context of Vaccination.

Journal Article American journal of epidemiology · November 2021 Assortativity is the tendency of individuals connected in a network to share traits and behaviors. Through simulations, we demonstrated the potential for bias resulting from assortativity by vaccination, where vaccinated individuals are more likely to be c ... Full text Cite

Multiple Imputation Using Gaussian Copulas

Journal Article Sociological Methods and Research · August 1, 2021 Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this article, we present a si ... Full text Cite

Author Clustering and Topic Estimation for Short Texts

Journal Article · June 15, 2021 Analysis of short text, such as social media posts, is extremely difficult because of their inherent brevity. In addition to classifying topics of such posts, a common downstream task is grouping the authors of these documents for subsequent analyses. We p ... Link to item Cite

SARS-CoV-2 Infection in Health Care Personnel and Their Household Contacts at a Tertiary Academic Medical Center: Protocol for a Longitudinal Cohort Study.

Journal Article JMIR research protocols · April 2021 BackgroundHealth care personnel (HCP) are at high risk for exposure to the SARS-CoV-2 virus. While personal protective equipment (PPE) may mitigate this risk, prospective data collection on its use and other risk factors for seroconversion in this ... Full text Cite

dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference

Journal Article · January 5, 2021 dame-flame is a Python package for performing matching for observational causal inference on datasets containing discrete covariates. This package implements the Dynamic Almost Matching Exactly (DAME) and Fast Large-Scale Almost Matching Exactly (FLAME) al ... Open Access Link to item Cite

FLAME: A fast large-scale almost matching exactly approach to causal inference

Journal Article Journal of Machine Learning Research · January 1, 2021 A classical problem in causal inference is that of matching, where treatment units need to be matched to control units based on covariate information. In this work, we propose a method that computes high quality almost-exact matches for high-dimensional ca ... Open Access Cite

The association between intersystem prison transfers and COVID-19 incidence in a state prison system.

Journal Article PLoS One · 2021 Prisons are the epicenter of the COVID-19 pandemic. Media reports have focused on whether transfers of incarcerated people between prisons have been the source of outbreaks. Our objective was to examine the relationship between intersystem prison transfers ... Full text Link to item Cite

SARS-CoV-2 Infection in Health Care Personnel and Their Household Contacts at a Tertiary Academic Medical Center: Protocol for a Longitudinal Cohort Study (Preprint)

Journal Article · November 17, 2020 BACKGROUNDHealth care personnel (HCP) are at high risk for exposure to the SARS-CoV-2 virus. While personal protective equipment (PPE) may mitigate this risk, prospective data collection ... Full text Cite

Designs for estimating the treatment effect in networks with interference

Journal Article Annals of Statistics · January 1, 2020 In this paper, we introduce new, easily implementable designs for drawing causal inference from randomized experiments on networks with interference. Inspired by the idea of matching in observational studies, we introduce the notion of considering a treatm ... Full text Cite

SMOGS: Social network metrics of game success

Journal Article AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics · January 1, 2020 In this paper we propose a novel metric of basketball game success, derived from a team's dynamic social network of game play. We combine ideas from random effects models for network links with taking a multi-resolution stochastic process approach to model ... Cite

Assessing the Russian Internet Research Agency's impact on the political attitudes and behaviors of American Twitter users in late 2017.

Journal Article Proceedings of the National Academy of Sciences of the United States of America · January 2020 There is widespread concern that Russia and other countries have launched social-media campaigns designed to increase political divisions in the United States. Though a growing number of studies analyze the strategy of such campaigns, it is not yet known h ... Full text Cite

Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation

Journal Article CONFERENCE ON UNCERTAINTY IN ARTIFICIAL INTELLIGENCE (UAI 2020) · 2020 Open Access Cite

Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference

Journal Article INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 108 · 2020 Cite

Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference

Conference Proceedings of Machine Learning Research · January 1, 2020 We propose a matching method that recovers direct treatment effects from randomized experiments where units are connected in an observed network, and units that share edges can potentially influence each others' outcomes. Traditional treatment effect estim ... Cite

Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation

Conference Proceedings of Machine Learning Research · January 1, 2020 We propose a matching method for observational data that matches units with others in unit-specific, hyper-box-shaped regions of the covariate space. These regions are large enough that many matches are created for each unit and small enough that the treat ... Cite

Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise

Journal Article 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings · December 1, 2019 Community detection tasks have received a lot of attention across statistics, machine learning, and information theory with work concentrating on providing theoretical guarantees for different methodological approaches to the stochastic block model. Recent ... Full text Cite

The Geometry of Community Detection via the MMSE Matrix

Journal Article IEEE International Symposium on Information Theory - Proceedings · July 1, 2019 The information-theoretic limits of community detection have been studied extensively for network models with high levels of symmetry or homogeneity. The contribution of this paper is to study a broader class of network models that allow for variability in ... Full text Cite

Interpretable Almost-Exact Matching for Causal Inference.

Journal Article Proceedings of machine learning research · April 2019 Matching methods are heavily used in the social and health sciences due to their interpretability. We aim to create the highest possible quality of treatment-control matches for categorical data in the potential outcomes framework. The method proposed in t ... Cite

Interpretable almost-matching-exactly with instrumental variables

Journal Article 35th Conference on Uncertainty in Artificial Intelligence, UAI 2019 · January 1, 2019 © 2019 Association For Uncertainty in Artificial Intelligence (AUAI). All rights reserved. Uncertainty in the estimation of the causal effect in observational studies is often due to unmeasured confounding, i.e., the presence of unobserved covariates linki ... Cite

Interpretable almost-matching-exactly with instrumental variables

Conference 35th Conference on Uncertainty in Artificial Intelligence, UAI 2019 · January 1, 2019 Uncertainty in the estimation of the causal effect in observational studies is often due to unmeasured confounding, i.e., the presence of unobserved covariates linking treatments and outcomes. Instrumental Variables (IV) are commonly used to reduce the eff ... Cite

MALTS: Matching After Learning to Stretch

Journal Article Journal.of.Machine.Learning.Research 23(240) (2022) 1-42 · November 18, 2018 We introduce a flexible framework that produces high-quality almost-exact matches for causal inference. Most prior work in matching uses ad-hoc distance metrics, often leading to poor quality matches, particularly when there are irrelevant covariates. In t ... Link to item Cite

Exposure to opposing views on social media can increase political polarization.

Journal Article Proceedings of the National Academy of Sciences of the United States of America · September 2018 There is mounting concern that social media sites contribute to political polarization by creating "echo chambers" that insulate people from opposing views about current events. We surveyed a large sample of Democrats and Republicans who visit Twitter at l ... Full text Open Access Cite

Interpretable Almost Matching Exactly for Causal Inference

Journal Article · June 18, 2018 We aim to create the highest possible quality of treatment-control matches for categorical data in the potential outcomes framework. Matching methods are heavily used in the social sciences due to their interpretability, but most matching methods do not pa ... Link to item Cite

Propensity score methodology in the presence of network entanglement between treatments

Journal Article · January 22, 2018 In experimental design and causal inference, it may happen that the treatment is not defined on individual experimental units, but rather on pairs or, more generally, on groups of units. For example, teachers may choose pairs of students who do not know ea ... Link to item Cite

Sharp total variation bounds for finitely exchangeable arrays

Journal Article Statistics and Probability Letters · July 1, 2016 In this article we demonstrate the relationship between finitely exchangeable arrays and finitely exchangeable sequences. We then derive sharp bounds on the total variation distance between distributions of finitely and infinitely exchangeable arrays. ... Full text Open Access Cite

Networks

Chapter · February 22, 2016 Cite

Observational studies with unknown time of treatment

Journal Article · January 15, 2016 Time plays a fundamental role in causal analyses, where the goal is to quantify the effect of a specific treatment on future outcomes. In a randomized experiment, times of treatment, and when outcomes are observed, are typically well defined. In an observa ... Link to item Cite

Analyzing statistical and computational tradeoffs of estimation procedures

Journal Article · June 25, 2015 The recent explosion in the amount and dimensionality of data has exacerbated the need of trading off computational and statistical efficiency carefully, so that inference is both tractable and meaningful. We propose a framework that provides an explicit o ... Link to item Cite

Causal inference for ordinal outcomes

Journal Article · January 6, 2015 Many outcomes of interest in the social and health sciences, as well as in modern applications in computational social science and experimentation on social media platforms, are ordinal and do not have a meaningful scale. Causal analyses that leverage this ... Link to item Cite

Testing for nodal dependence in relational data matrices.

Journal Article Journal of the American Statistical Association · January 2015 Relational data are often represented as a square matrix, the entries of which record the relationships between pairs of objects. Many statistical methods for the analysis of such data assume some degree of similarity or dependence between objects in terms ... Full text Cite

HIERARCHICAL ARRAY PRIORS FOR ANOVA DECOMPOSITIONS OF CROSS-CLASSIFIED DATA.

Journal Article The annals of applied statistics · March 2014 ANOVA decompositions are a standard method for describing and estimating heterogeneity among the means of a response variable across levels of multiple categorical factors. In such a decomposition, the complete set of main effects and interaction terms can ... Full text Cite

Likelihoods for fixed rank nomination networks.

Journal Article Network science (Cambridge University Press) · December 2013 Many studies that gather social network data use survey methods that lead to censored, missing, or otherwise incomplete information. For example, the popular fixed rank nomination (FRN) scheme, often used in studies of schools and businesses, asks study pa ... Full text Cite

Likelihoods for fixed rank nomination networks

Journal Article Network Science · December 2013 Cite