Scholars@Duke
Fan Li

Fan Li

Professor of Statistical Science
Statistical Science
fl35@duke.edu
Box 90251, Durham, NC 27708-0251
122 Old Chem Bldg, Durham, NC 27708

Selected Publications

Association between first anticoagulant prescription and embolic and hemorrhagic events among older adults with atrial fibrillation.

Journal Article J Intern Med · January 2026 BACKGROUND: The impact of first prescription of oral anticoagulation on ischemic stroke and major bleeding events among Medicare beneficiaries with atrial fibrillation (AF) is not known. METHODS: A retrospective, observational, cohort study was performed b ... Full text Link to item Cite

Public Health.

Journal Article Alzheimers Dement · December 2025 BACKGROUND: Anti-amyloid monoclonal antibodies (lecanemab and donanemab) received full approval by the FDA to treat early Alzheimer's disease and entered routine clinical practice in July 2023 and July 2024 respectively. Uptake patterns and post-approval s ... Full text Link to item Cite

Abstract 4370283: Real-World Effectiveness of GLP-1 Receptor Agonists on Clinical Outcomes in Patients with Heart Failure with Preserved Ejection Fraction (HFpEF).

Conference Circulation · November 4, 2025 Introduction/Background: Multiple clinical trials have demonstrated that glucagon-like peptide 1 receptor agonists (GLP-1 Ras) improve symptoms, physical function, and potentially redu ... Full text Cite

Abstract 4367284: Hospital Admissions With Hypertensive Emergency Increased While Admissions With Asymptomatic Elevated Inpatient Blood Pressure Decreased From 2014-2024: A Nationwide Study

Conference Circulation · November 4, 2025 Introduction: Hypertension is common in acute care settings, and there is controversy on the best management depending on severity of elevation and the presence of end-organ damage, as ... Full text Cite

Hospital Implementation of Endovascular Thrombectomy and Health Equity in Acute Stroke Outcomes.

Journal Article Stroke · November 2025 BACKGROUND: The introduction of novel therapeutics into clinical practice could impact equity in health outcomes. METHODS: This was a retrospective, observational cohort study based on the Get With The Guidelines-Stroke program of the American Heart Associ ... Full text Link to item Cite

Sex Differences in Mortality and Health Care Utilization After Dementia Diagnosis.

Journal Article JAMA Neurol · October 1, 2025 IMPORTANCE: Sex differences may contribute to disparities in dementia outcomes. OBJECTIVE: To understand the association between sex and mortality and health care services use after dementia diagnosis. DESIGN, SETTING, AND PARTICIPANTS: This nationwide coh ... Full text Link to item Cite

Implementation of the ICH E9 (R1) addendum in vaccine efficacy studies: the hypothetical and principal stratum strategies.

Journal Article Journal of biopharmaceutical statistics · October 2025 Over the past decades, the primary interest in vaccine efficacy evaluation has mostly been on the effect observed in trial participants complying with the protocol requirements (per protocol analysis). The ICH E9 (R1) addendum provides a structured framewo ... Full text Cite

Development of a natural language processing algorithm to extract social determinants of health from clinician notes.

Journal Article Am J Transplant · June 2025 Disparities in access to the organ transplant waitlist are well-documented, but research into modifiable factors has been limited due to a lack of access to organized prewaitlisting data. This study aimed to develop a natural language processing (NLP) algo ... Full text Link to item Cite

Incidence and prevalence of dementia among US Medicare beneficiaries, 2015-21: population based study.

Journal Article BMJ · May 20, 2025 OBJECTIVE: To determine the incidence and prevalence of dementia in a nationally representative cohort of US Medicare beneficiaries, stratified by important subgroups. DESIGN: Population based study. SETTING: Nationwide study between 2015 and 2021. PARTICI ... Full text Link to item Cite

Application of unified health large language model evaluation framework to In-Basket message replies: bridging qualitative and quantitative assessments.

Journal Article J Am Med Inform Assoc · April 1, 2025 OBJECTIVES: Large language models (LLMs) are increasingly utilized in healthcare, transforming medical practice through advanced language processing capabilities. However, the evaluation of LLMs predominantly relies on human qualitative assessment, which i ... Full text Link to item Cite

Random Survival Forest Machine Learning for the Prediction of Cardiovascular Events Among Patients With a Measured Lipoprotein(a) Level: A Model Development Study.

Journal Article Circ Genom Precis Med · February 2025 BACKGROUND: Established risk models may not be applicable to patients at higher cardiovascular risk with a measured Lp(a) (lipoprotein[a]) level, a causal risk factor for atherosclerotic cardiovascular disease. METHODS: This was a model development study. ... Full text Link to item Cite

Atrial Fibrillation and Retinal Stroke.

Journal Article JAMA Netw Open · January 2, 2025 IMPORTANCE: Atrial fibrillation (AF) is the most common, chronic, cardiac arrythmia in older US adults. It is not known whether AF is independently associated with increased risk of retinal stroke (central retinal artery occlusion), a subtype of ischemic s ... Full text Link to item Cite

Addressing selection bias in cluster randomized experiments via weighting.

Journal Article Biometrics · January 2025 In cluster randomized experiments, individuals are often recruited after the cluster treatment assignment, and data are typically only available for the recruited sample. Post-randomization recruitment can lead to selection bias, inducing systematic differ ... Full text Cite

Covariate adjustment in randomized experiments with missing outcomes and covariates

Journal Article Biometrika · December 1, 2024 Covariate adjustment can improve precision in analysing randomized experiments. With fully observed data, regression adjustment and propensity score weighting are asymptotically equivalent in improving efficiency over unadjusted analysis. When some outcome ... Full text Cite

Mobile Stroke Unit Management in Patients With Acute Ischemic Stroke Eligible for Intravenous Thrombolysis.

Journal Article JAMA Neurol · December 1, 2024 IMPORTANCE: Clinical trials have suggested that prehospital management in a mobile stroke unit (MSU) improves functional outcomes in patients with acute ischemic stroke who are potentially eligible for intravenous thrombolysis, but there is a paucity of re ... Full text Link to item Cite

Multiply robust estimation of principal causal effects with noncompliance and survival outcomes.

Journal Article Clin Trials · October 2024 Treatment noncompliance and censoring are two common complications in clinical trials. Motivated by the ADAPTABLE pragmatic clinical trial, we develop methods for assessing treatment effects in the presence of treatment noncompliance with a right-censored ... Full text Link to item Cite

Principal stratification analysis of noncompliance with time-to-event outcomes.

Journal Article Biometrics · January 29, 2024 Post-randomization events, also known as intercurrent events, such as treatment noncompliance and censoring due to a terminal event, are common in clinical trials. Principal stratification is a framework for causal inference in the presence of intercurrent ... Full text Link to item Cite

A note on identification of causal effects in cluster randomized trials with post-randomization selection bias

Journal Article Communications in Statistics Theory and Methods · January 1, 2024 Cluster randomized trials are commonly used for evaluating treatment effects of a cluster-level intervention. Because subjects are often recruited after cluster randomization, a main complication is the potential for selection bias due to the intervention ... Full text Cite

Propensity score weighting methods for causal subgroup analysis with time-to-event outcomes.

Journal Article Stat Methods Med Res · October 2023 Evaluating causal effects of an intervention in pre-specified subgroups is a standard goal in comparative effectiveness research. Despite recent advancements in causal subgroup analysis, research on time-to-event outcomes has been lacking. This article inv ... Full text Link to item Cite

Covariate adjustment in randomized clinical trials with missing covariate and outcome data.

Journal Article Statistics in medicine · September 2023 When analyzing data from randomized clinical trials, covariate adjustment can be used to account for chance imbalance in baseline covariates and to increase precision of the treatment effect estimate. A practical barrier to covariate adjustment is the pres ... Full text Cite

PROPENSITY SCORE WEIGHTING ANALYSIS OF SURVIVAL OUTCOMES USING PSEUDO-OBSERVATIONS

Journal Article Statistica Sinica · July 1, 2023 Survival outcomes are common in comparative effectiveness studies and require unique handling, because they are usually incompletely observed owing to right-censoring. A “once for all” approach for causal inference with survival outcomes constructs pseudo- ... Full text Cite

A Causal Mediation Model for Longitudinal Mediators and Survival Outcomes with an Application to Animal Behavior.

Journal Article Journal of agricultural, biological, and environmental statistics · June 2023 In animal behavior studies, a common goal is to investigate the causal pathways between an exposure and outcome, and a mediator that lies in between. Causal mediation analysis provides a principled approach for such studies. Although many applications invo ... Full text Cite

Bayesian causal inference: a critical review.

Journal Article Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · May 2023 This paper provides a critical review of the Bayesian perspective of causal inference based on the potential outcomes framework. We review the causal estimands, assignment mechanism, the general structure of Bayesian inference of causal effects and sensiti ... Full text Cite

Early life adversity and adult social relationships have independent effects on survival in a wild primate.

Journal Article Science advances · May 2023 Adverse conditions in early life can have negative consequences for adult health and survival in humans and other animals. What variables mediate the relationship between early adversity and adult survival? Adult social environments represent one candidate ... Full text Cite

Using propensity scores for racial disparities analysis

Journal Article Observational Studies · January 1, 2023 Propensity score plays a central role in causal inference, but its use is not limited to causal comparisons. As a covariate balancing tool, propensity score can be used for controlled descriptive comparisons between groups whose memberships are not manipul ... Full text Cite

Overlap Weighting

Chapter · January 1, 2023 This chapter allows analysts to flexibly specify a target population first and then estimate the corresponding treatment effect. It focuses on a special case of balancing weights, the overlap weight, which possesses desirable theoretical and empirical prop ... Full text Cite

Atrial fibrillation as a novel risk factor for retinal stroke: A protocol for a population-based retrospective cohort study.

Journal Article PLoS One · 2023 Central retinal artery occlusion (CRAO; retinal stroke or eye stroke) is an under-recognized, disabling form of acute ischemic stroke which causes severe visual loss in one eye. The classical risk factor for CRAO is ipsilateral carotid stenosis; however, n ... Full text Link to item Cite

Causal inference with spatio-temporal data: Estimating the effects of airstrikes on insurgent violence in Iraq

Journal Article Journal of the Royal Statistical Society Series B Statistical Methodology · November 1, 2022 Many causal processes have spatial and temporal dimensions. Yet the classic causal inference framework is not directly applicable when the treatment and outcome variables are generated by spatio-temporal point processes. We extend the potential outcomes fr ... Full text Cite

Causal analysis of central bank holdings of corporate bonds under interference

Journal Article Economic Modelling · August 1, 2022 We investigate whether the transfer of corporate bonds from the private sector to the balance sheet of the central bank permanently alters their relative prices. Answering this question complements the literature on central bank asset purchase programs, do ... Full text Cite

Addressing Extreme Propensity Scores in Estimating Counterfactual Survival Functions via the Overlap Weights.

Journal Article Am J Epidemiol · May 20, 2022 The inverse probability of treatment weighting (IPTW) approach is popular for evaluating causal effects in observational studies, but extreme propensity scores could bias the estimator and induce excessive variance. Recently, the overlap weighting approach ... Full text Link to item Cite

PSweight: An R Package for Propensity ScoreWeighting Analysis

Journal Article R Journal · March 1, 2022 Propensity score weighting is an important tool for comparative effectiveness research. Besides the inverse probability of treatment weights (IPW), recent development has introduced a general class of balancing weights, corresponding to alternative target ... Full text Cite

Clarifying selection bias in cluster randomized trials.

Journal Article Clinical trials (London, England) · February 2022 BackgroundIn cluster randomized trials, patients are typically recruited after clusters are randomized, and the recruiters and patients may not be blinded to the assignment. This often leads to differential recruitment and consequently systematic ... Full text Cite

Are deep learning models superior for missing data imputation in surveys? Evidence from an empirical comparison

Journal Article Survey Methodology · January 1, 2022 Multiple imputation (MI) is a popular approach for dealing with missing data arising from non-response in sample surveys. Multiple imputation by chained equations (MICE) is one of the most widely used MI algorithms for multivariate data, but it lacks theor ... Cite

Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization

Conference Advances in Neural Information Processing Systems · January 1, 2022 Successful applications of InfoNCE (Information Noise-Contrastive Estimation) and its variants have popularized the use of contrastive variational mutual information (MI) estimators in machine learning. While featuring superior stability, these estimators ... Cite

Covariate adjustment in subgroup analyses of randomized clinical trials: A propensity score approach.

Journal Article Clin Trials · October 2021 BACKGROUND: Subgroup analyses are frequently conducted in randomized clinical trials to assess evidence of heterogeneous treatment effect across patient subpopulations. Although randomization balances covariates within subgroups in expectation, chance imba ... Full text Link to item Cite

Propensity score weighting for causal subgroup analysis.

Journal Article Stat Med · August 30, 2021 A common goal in comparative effectiveness research is to estimate treatment effects on prespecified subpopulations of patients. Though widely used in medical research, causal inference methods for such subgroup analysis (SGA) remain underdeveloped, partic ... Full text Link to item Cite

Hölder Bounds for Sensitivity Analysis in Causal Reasoning

Journal Article · July 9, 2021 We examine interval estimation of the effect of a treatment T on an outcome Y given the existence of an unobserved confounder U. Using H\"older's inequality, we derive a set of bounds on the confounding bias |E[Y|T=t]-E[Y|do(T=t)]| based on the degree of u ... Open Access Link to item Cite

CAUSAL MEDIATION ANALYSIS FOR SPARSE AND IRREGULAR LONGITUDINAL DATA.

Journal Article The annals of applied statistics · June 2021 Causal mediation analysis seeks to investigate how the treatment effect of an exposure on outcomes is mediated through intermediate variables. Although many applications involve longitudinal data, the existing methods are not directly applicable to setting ... Full text Cite

Propensity score weighting for covariate adjustment in randomized clinical trials.

Journal Article Statistics in medicine · February 2021 Chance imbalance in baseline characteristics is common in randomized clinical trials. Regression adjustment such as the analysis of covariance (ANCOVA) is often used to account for imbalance and increase precision of the treatment effect estimate. An objec ... Full text Cite

A regression discontinuity design for ordinal running variables: Evaluating central bank purchases of corporate bonds

Journal Article Annals of Applied Statistics · January 1, 2021 Regression discontinuity (RD) is a widely used quasi-experimental design for causal inference. In the standard RD the assignment to treatment is determined by a continuous pretreatment variable (i.e., running variable) falling above or below a prefixed thr ... Full text Cite

Counterfactual Representation Learning with Balancing Weights

Journal Article Proceedings of Machine Learning Research · January 1, 2021 A key to causal inference with observational data is achieving balance in predictive features associated with each treatment type. Recent literature has explored representation learning to achieve this goal. In this work, we discuss the pitfalls of these s ... Cite

Effects of Eligibility for Central Bank Purchases on Corporate Bond Spreads

Journal Article Bank of Italy Temi di Discussione (Working Paper) · November 11, 2020 Cite

Reduction in healthcare services during the COVID-19 pandemic in China.

Journal Article BMJ Glob Health · November 2020 INTRODUCTION: The COVID-19 pandemic caused a healthcare crisis in China and continues to wreak havoc across the world. This paper evaluated COVID-19's impact on national and regional healthcare service utilisation and expenditure in China. METHODS: Using a ... Full text Link to item Cite

Is being an only child harmful to psychological health?: evidence from an instrumental variable analysis of China's one-child policy

Journal Article Journal of the Royal Statistical Society Series A Statistics in Society · October 1, 2020 The paper evaluates the effects of being an only child in a family on psychological health, leveraging data on the one-child policy in China. We use an instrumental variable approach to address the potential unmeasured confounding between the fertility dec ... Full text Cite

Evaluating the causal effects of cellphone distraction on crash risk using propensity score methods.

Journal Article Accident; analysis and prevention · August 2020 Introduction/objectiveThis paper evaluates the causal effects of cellphone distraction on traffic crashes using propensity score weighting approaches and naturalistic driving study (NDS) data.MethodsWe adopt three propensity score weighti ... Full text Cite

Social bonds do not mediate the relationship between early adversity and adult glucocorticoids in wild baboons.

Journal Article Proceedings of the National Academy of Sciences of the United States of America · August 2020 In humans and other animals, harsh conditions in early life can have profound effects on adult physiology, including the stress response. This relationship may be mediated by a lack of supportive relationships in adulthood. That is, early life adversity ma ... Full text Cite

Subgroup balancing propensity score.

Journal Article Statistical methods in medical research · March 2020 This paper concerns estimation of subgroup treatment effects with observational data. Existing propensity score methods are mostly developed for estimating overall treatment effect. Although the true propensity scores balance covariates in any subpopulatio ... Full text Cite

Reconsidering generative objectives for counterfactual reasoning

Conference Advances in Neural Information Processing Systems · January 1, 2020 There has been recent interest in exploring generative goals for counterfactual reasoning, e.g., individualized treatment effect (ITE) estimation. However, existing solutions often fail to address issues that are unique to causal inference, such as covaria ... Cite

A Bracketing Relationship between Difference-in-Differences and Lagged-Dependent-Variable Adjustment

Journal Article Political Analysis · October 1, 2019 Difference-in-differences is a widely used evaluation strategy that draws causal inference from observational panel data. Its causal identification relies on the assumption of parallel trends, which is scale-dependent and may be questionable in some applic ... Full text Cite

Disease Mapping With Generative Models

Journal Article American Statistician · July 3, 2019 Disease mapping focuses on learning about areal units presenting high relative risk. Disease mapping models assume that the disease counts are distributed as Poisson random variables with the respective means typically specified as the product of the relat ... Full text Cite

Discussion of “Penalized Spline of Propensity Methods for Treatment Comparison”

Journal Article Journal of the American Statistical Association · January 2, 2019 Full text Cite

Addressing Extreme Propensity Scores via the Overlap Weights.

Journal Article Am J Epidemiol · January 1, 2019 The popular inverse probability weighting method in causal inference is often hampered by extreme propensity scores, resulting in biased estimates and excessive variance. A common remedy is to trim patients with extreme scores (i.e., remove them from the w ... Full text Link to item Cite

Double-Robust Estimation in Difference-in-Differences with an Application to Traffic Safety Evaluation

Journal Article Observational Studies · January 1, 2019 Difference-in-differences (DID) is a widely used approach for drawing causal inference from observational panel data. Two common estimation strategies for DID are outcome regression and propensity score weighting. In this paper, motivated by a real applica ... Full text Cite

Predicting Quality of Life at 1 Year After Transcatheter Aortic Valve Replacement in a Real-World Population.

Journal Article Circ Cardiovasc Qual Outcomes · October 2018 Background Among clinical trial patients at high surgical risk, a model has been developed and externally validated to estimate patient risk for poor outcomes after transcatheter aortic valve replacement (TAVR). How this model performs in lower risk and un ... Full text Link to item Cite

Predicting Length of Hospice Stay: An Application of Quantile Regression.

Journal Article J Palliat Med · August 2018 BACKGROUND: Use of the Medicare hospice benefit has been associated with high-quality care at the end of life, and hospice length of use in particular has been used as a proxy for appropriate timing of hospice enrollment. Quantile regression has been under ... Full text Link to item Cite

Causal inference: A missing data perspective

Journal Article Statistical Science · May 1, 2018 Inferring causal effects of treatments is a central goal in many disciplines. The potential outcomes framework is a main statistical approach to causal inference, in which a causal effect is defined as a comparison of the potential outcomes of the same uni ... Full text Cite

Balancing Covariates via Propensity Score Weighting

Journal Article Journal of the American Statistical Association · January 2, 2018 Covariate balance is crucial for unconfounded descriptive or causal comparisons. However, lack of balance is common in observational studies. This article considers weighting strategies for balancing covariates. We define a general class of weights—the bal ... Full text Cite

Accommodating the ecological fallacy in disease mapping in the absence of individual exposures.

Journal Article Statistics in medicine · December 2017 In health exposure modeling, in particular, disease mapping, the ecological fallacy arises because the relationship between aggregated disease incidence on areal units and average exposure on those units differs from the relationship between the event of i ... Full text Open Access Cite

Do debit cards decrease cash demand?: causal inference and sensitivity analysis using principal stratification

Journal Article Journal of the Royal Statistical Society Series C Applied Statistics · August 1, 2017 It has been argued that the use of debit cards may modify cash holding behaviour, as debit card holders may either withdraw cash from automated teller machines or purchase items by using point-of-sale devices at retailers. Within the Rubin causal model, we ... Full text Cite

Transcatheter Versus Surgical Aortic Valve Replacement: Propensity-Matched Comparison.

Journal Article J Am Coll Cardiol · July 25, 2017 BACKGROUND: Randomized trials support the use of transcatheter aortic valve replacement (TAVR) for the treatment of aortic stenosis in high- and intermediate-risk patients, but the generalizability of those results in clinical practice has been challenged. ... Full text Link to item Cite

An Empirical Comparison of Multiple Imputation Methods for Categorical Data

Journal Article American Statistician · April 3, 2017 Multiple imputation is a common approach for dealing with missing values in statistical databases. The imputer fills in missing values with draws from predictive models estimated from the observed data, resulting in multiple, completed versions of the data ... Full text Open Access Cite

Evaluating the causal effect of university grants on student dropout: Evidence from a regression discontinuity design using principal stratification

Journal Article Annals of Applied Statistics · December 1, 2015 Regression discontinuity (RD) designs are often interpreted as locally randomized experiments for units with a realized value of a pretreatment variable falling around a threshold. Motivated by the evaluation of Italian university grants, we consider a fuz ... Full text Cite

Spatial Bayesian variable selection and grouping for high-dimensional scalar-on-image regression

Journal Article Annals of Applied Statistics · June 1, 2015 Multi-subject functional magnetic resonance imaging (fMRI) data has been increasingly used to study the population-wide relationship between human brain activity and individual biological or behavioral traits. A common method is to regress the scalar indiv ... Full text Cite

A Dynamic Directional Model for Effective Brain Connectivity using Electrocorticographic (ECoG) Time Series.

Journal Article Journal of the American Statistical Association · March 2015 We introduce a dynamic directional model (DDM) for studying brain effective connectivity based on intracranial electrocorticographic (ECoG) time series. The DDM consists of two parts: a set of differential equations describing neuronal activity of brain co ... Full text Open Access Cite

Improving inference of Gaussian mixtures using auxiliary variables

Journal Article Statistical Analysis and Data Mining · February 1, 2015 Expanding a lower-dimensional problem to a higher-dimensional space and then projecting back is often beneficial. This article rigorously investigates this perspective in the context of finite mixture models, specifically how to improve inference for mixtu ... Full text Cite

Do debit cards increase household spending? Evidence from a semiparametric causal analysis of a survey

Journal Article Annals of Applied Statistics · December 1, 2014 Motivated by recent findings in the field of consumer science, this paper evaluates the causal effect of debit cards on household consumption using population-based data from the Italy Survey on Household Income and Wealth (SHIW). Within the Rubin Causal M ... Full text Open Access Cite

Modeling individual tree growth by fusing diameter tape and increment core data

Journal Article Environmetrics · December 1, 2014 Tree growth estimation is a challenging task as difficulties associated with data collection and inference often result in inaccurate estimates. Two main methods for tree growth estimation are diameter tape measurements and increment cores. The former invo ... Full text Cite

A semi-parametric nonlinear model for event-related fMRI.

Journal Article NeuroImage · August 2014 Nonlinearity in evoked hemodynamic responses often presents in event-related fMRI studies. Volterra series, a higher-order extension of linear convolution, has been used in the literature to construct a nonlinear characterization of hemodynamic responses. ... Full text Cite

Multiple Imputation by Ordered Monotone Blocks With Application to the Anthrax Vaccine Research Program

Journal Article Journal of Computational and Graphical Statistics · July 3, 2014 Multiple imputation (MI) has become a standard statistical technique for dealing with missing values. The CDC Anthrax Vaccine Research Program (AVRP) dataset created new challenges for MI due to the large number of variables of different types and the limi ... Full text Cite

Bayesian regularization via graph Laplacian

Journal Article Bayesian Analysis · January 1, 2014 Regularization plays a critical role in modern statistical research, especially in high-dimensional variable selection problems. Existing Bayesian methods usually assume independence between variables a priori. In this article, we propose a novel Bayesian ... Full text Cite

A conversation with Donald B. Rubin

Journal Article Statistical Science · January 1, 2014 Donald Bruce Rubin is John L. Loeb Professor of Statistics at Harvard University. He has made fundamental contributions to statistical methods for missing data, causal inference, survey sampling, Bayesian inference, computing and applications to a wide ran ... Full text Cite

Exploiting multiple outcomes in Bayesian principal stratification analysis with application to the evaluation of a job training program

Journal Article Annals of Applied Statistics · December 1, 2013 The causal effect of a randomized job training program, the JOBS II study, on trainees' depression is evaluated. Principal stratification is used to deal with noncompliance to the assigned treatment. Due to the latent nature of the principal strata, strong ... Full text Cite

Propensity score weighting with multilevel data.

Journal Article Statistics in medicine · August 2013 Propensity score methods are being increasingly used as a less parametric alternative to traditional regression to balance observed differences across groups in both descriptive and causal comparisons. Data collected in many disciplines often have analytic ... Full text Cite

A semi-parametric model of the hemodynamic response for multi-subject fMRI data.

Journal Article NeuroImage · July 2013 A semi-parametric model for estimating hemodynamic response function (HRF) from multi-subject fMRI data is introduced within the context of the General Linear Model. The new model assumes that the HRFs for a fixed brain voxel under a given stimulus share t ... Full text Cite

Nonparametric inference of the hemodynamic response using multi-subject fMRI data.

Journal Article NeuroImage · November 2012 Estimation and inferences for the hemodynamic response functions (HRF) using multi-subject fMRI data are considered. Within the context of the General Linear Model, two new nonparametric estimators for the HRF are proposed. The first is a kernel-smoothed e ... Full text Cite

Sensitivity analysis for unmeasured confounding in principal stratification settings with binary variables.

Journal Article Statistics in medicine · May 2012 Within causal inference, principal stratification (PS) is a popular approach for dealing with intermediate variables, that is, variables affected by treatment that also potentially affect the response. However, when there exists unmeasured confounding in t ... Full text Cite

A bayesian semiparametric approach to intermediate variables in causal inference

Journal Article Journal of the American Statistical Association · December 1, 2011 In causal inference studies, treatment comparisons often need to be adjusted for confounded post-treatment variables. Principal stratification (PS) is a framework to deal with such variables within the potential outcome approach to causal inference. Contin ... Full text Cite

Characteristics of high-risk HIV-positive IDUs in Vietnam: implications for future interventions.

Journal Article Substance use & misuse · January 2011 The HIV epidemic in Vietnam is concentrated primarily among injecting drug users (IDUs). To prevent HIV-1 superinfection and to develop effective HIV prevention programs, data are needed to understand the characteristics of high-risk HIV-positive IDUs. In ... Full text Cite

Using a short screening scale for small-area estimation of mental illness prevalence for schools.

Journal Article Journal of the American Statistical Association · December 2010 We use data collected in the National Comorbidity Survey - Adolescent (NCS-A) to develop a methodology to estimate the small-area prevalence of serious emotional distress (SED) in schools in the United States, exploiting the clustering of the main NCS-A sa ... Full text Cite

Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics

Journal Article Journal of the American Statistical Association · September 1, 2010 We consider the problem of variable selection in regression modeling in high-dimensional spaces where there is known structure among the covariates. This is an unconventional variable selection problem for two reasons: (1) The dimension of the covariate sp ... Full text Open Access Cite

Estimating prevalence of serious emotional disturbance in schools using a brief screening scale.

Journal Article International journal of methods in psychiatric research · June 2010 Information about the prevalence of serious mental illness (SMI) among adults or serious emotional disturbance (SED) among youth in small domains such as counties, states, or schools is valuable for mental health policy planning purposes, but prohibitively ... Full text Cite

Polydesigns and causal inference.

Journal Article Biometrics · June 2006 In an increasingly common class of studies, the goal is to evaluate causal effects of treatments that are only partially controlled by the investigator. In such studies there are two conflicting features: (1) a model on the full cohort design and data can ... Full text Cite

Designs in partially controlled studies: messages from a review.

Journal Article Statistical methods in medical research · August 2005 The ability to evaluate effects of factors on outcomes is increasingly important for studies that control some but not all of the factors. Although important advances have been made in methods of analysis for such partially controlled studies, work on desi ... Full text Cite

Propensity Score Weighting for Causal Inference with Multi-valued Treatments

Journal Article This article proposes a unified framework, the balancing weights, for estimating causal effects with multi-valued treatments using propensity score weighting. These weights incorporate the generalized propensity score to balance the weighted covariate dist ... Link to item Cite