James O'Malley

Professor of Biostatistics

Dartmouth College Geisel School of Medicine

United States

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James O'Malley is a Professor of Biostatistics at Dartmouth College Geisel School of Medicine in the United States. His research focuses on advanced statistical methodologies, including Bayesian estimation techniques, network autocorrelation models, and telehealth adoption. Recent articles highlight his work on the impact of network structures on peer effects, as well as the implications of rural oncology care delivery. He is actively engaged in studying public health trends and methodologies related to healthcare optimization.

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Glyn Elwyn

Dartmouth College

UNITED STATES

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Tracy Onega

UNITED STATES

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seonjoo lee

Associate Professor of Clinical Biostatistics (in Psychiatry)

Columbia University

UNITED STATES

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Eric Roberts

University of Pittsburgh

UNITED STATES

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Zhigang Li

UNITED STATES

Dean's Postdoctoral Research Associate

The University of Alabama

UNITED STATES

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James O'Malley

Research Interests

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Articles (20)

Primary Care Practice Factors Associated With Telehealth Adoption in the United States: Cross-Sectional Survey Analysis

Influence of multiple network structures on bayesian estimation of peer effects and statistical power for generalized linear network autocorrelation models

A Bayesian zero-inflated spatially varying coefficients model for overdispersed binomial data

Rural Oncologists' Perceptions of Specialty Scarcity and Repercussions for Care Delivery: A Qualitative Study

Methodology for supervised optimization of the construction of physician shared-patient networks

National Trends in Stroke Presentation, Treatments, and Outcomes During the First 2 Years of the COVID-19 Pandemic

Developing and Comparing Four Families of Bayesian Network Autocorrelation Models for Binary Outcomes: Estimating Peer Effects Involving Adoption of Medical Technologies

Characterizing the Traveling Oncology Workforce and Its Influence on Patient Travel Burden: A Claims-Based Approach

Network spillover effects associated with the ChooseWell 365 workplace randomized controlled trial to promote healthy food choices

Clinician-Spoken Plain Language in Health Care Encounters: A Qualitative Analysis to Assess Measurable Elements

Exploiting relationship directionality to enhance statistical modeling of peer‐influence across social networks

Association between a network-based physician linchpin score and cancer patient mortality: a SEER-Medicare analysis

The diffusion of health care fraud: A bipartite network analysis

Telehealth Use Following COVID-19 Within Patient-Sharing Physician Networks at a Rural Comprehensive Cancer Center: Cross-sectional Analysis

A novel causal mediation analysis approach for zero‐inflated mediators

Discussion on “Instrumental variable estimation of the causal hazard ratio” by Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, and Stijn Vansteelandt

Obesity-Related Discourse on Facebook and Instagram Throughout the COVID-19 Pandemic: Comparative Longitudinal Evaluation

Characterizing the Prevalence of Obesity Misinformation, Factual Content, Stigma, and Positivity on the Social Media Platform Reddit Between 2011 and 2019: Infodemiology Study

Using a mixed‐effect model with a parameter‐space of heterogenous dimension to evaluate whether accountable care organizations are associated with greater uniformity across constituent practices

Weak correlations in health services research: Weak relationships or common error?

Collaborators (14)

HECTOR RODRIGUEZ

Gabriel Brooks

Jonathan Skinner

Mark Pachucki

Matthew Mackwood

Glyn Elwyn

Tracy Onega

seonjoo lee

Eric Roberts

Zhigang Li

Fahui Wang

Catherine H. Saunders

Jennifer Emond

Changzhen Wang

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