All SERplaylists
SERplaylists are curated collections of key papers and expert commentary on foundational topics in epidemiology. Designed by leaders in the field, these playlists offer a guided pathway through core methodological and substantive themes.
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Jay Kaufman explores the concept of selection bias in epidemiologic research. This article explains how systematic differences in study participation can distort findings and offers strategies to identify and mitigate bias in study design and analysis.
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Ali Rowhani-Rahbar explains self-controlled designs in epidemiologic research, focusing on methods that use individuals as their own controls. This article reviews applications, strengths, and limitations of these designs for studying transient exposures and outcomes.
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David Savitz examines epidemiologic studies on the health effects of electromagnetic fields. This article reviews evidence, methodological challenges, and research strategies for understanding potential risks associated with EMF exposure.
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Sean D. Cleary discusses the principles of collaboration and team science in research. This article highlights strategies for building effective interdisciplinary teams, fostering communication, and advancing scientific discovery through cooperative approaches.
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Shuji Ogino introduces molecular pathological epidemiology, an emerging field that integrates molecular biology with population-based research. This article explains how linking pathology and epidemiology can uncover disease mechanisms and improve precision medicine strategies.
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Jennifer Weuve of Rush University Medical Center explores tools and insights for studying cognitive aging and dementia. This article reviews epidemiologic approaches, measurement challenges, and strategies to advance research on brain health in aging populations.
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Charles Poole of the University of North Carolina highlights ten influential papers by Sander Greenland. This curated selection showcases foundational contributions to epidemiologic theory and methods, offering essential reading for researchers and students alike.
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Matthew P. Fox and Timothy L. Lash introduce quantitative bias analysis, a powerful approach for assessing the impact of systematic errors in epidemiologic research. This article explains methods to evaluate bias and strengthen study validity.
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Germaine M. Buck Louis examines human fecundity and fertility, focusing on biological and environmental factors that influence reproductive outcomes. This article provides insights into measurement challenges and implications for epidemiologic research.
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Lisa Bodnar of the University of Pittsburgh shares strategies for writing a successful grant proposal. This article offers practical guidance on crafting clear objectives, strong methodology, and compelling narratives to secure research funding.
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Jason Boardman of the University of Colorado, Boulder, discusses the role of sociological research in understanding health outcomes. This article explores how social structures and contexts shape population health and inform epidemiologic studies.
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Greatest Hits – Part 2 brings together standout conversations and resources from the EpiResearch community. This collection highlights influential discussions on epidemiologic methods and practical insights for researchers seeking quick access to key topics.
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Discover highlights from the EpiResearch community in Greatest Hits – Part 1. This curated collection features popular discussions and insights on epidemiologic methods and practice, offering quick access to foundational and trending topics.
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Lauren Wise of Boston University explores the complex relationship between fertility and pregnancy loss. This article reviews epidemiologic evidence, risk factors, and methodological challenges in studying reproductive health outcomes.
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Sherman James of Duke University examines racial and ethnic health disparities, exploring social determinants and their impact on population health. This article highlights structural factors contributing to inequities and offers insights for advancing health equity research.
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Explore the foundations of Marginal Structural Models in epidemiology. Stephen Cole, from the University of North Carolina at Chapel Hill, introduces key concepts and practical applications for causal inference in longitudinal studies.
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Learn the fundamentals of Bayesian methods in epidemiologic research with this introductory playlist. Authored by Richard MacLehose (University of Minnesota), it explains core concepts, practical applications, and advantages of Bayesian approaches for statistical analysis and decision-making.
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Continue the discussion on income inequality and health with Part 2 of this scholarly playlist. Authored by Ichiro Kawachi (Harvard University), this section explores deeper evidence and mechanisms linking economic disparities to health outcomes, offering critical insights for public health research and policy.
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Examine the relationship between income inequality and health in this insightful playlist. Authored by Ichiro Kawachi (Harvard University), Part 1 introduces key evidence and theoretical frameworks explaining how economic disparities shape population health outcomes. Essential reading for public health and policy professionals.
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Explore Consequentialist Epidemiology, a perspective that prioritizes real-world impact and ethical responsibility in research. Authored by Sandro Galea (Columbia University), this playlist examines how consequentialist thinking influences epidemiologic methods and decision-making to improve public health outcomes.
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Dive into the meaning and interpretation of p-values in statistical analysis with this scholarly playlist. Authored by Charles Poole (University of North Carolina, Chapel Hill), this resource clarifies common misconceptions and offers practical guidance for epidemiologic research and hypothesis testing.
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Delve deeper into competing risks in survival analysis with Part 2 of this scholarly playlist. Authored by Bryan Lau, this resource explores advanced concepts and practical applications for epidemiologic research, helping analysts address complex time-to-event data challenges.
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Explore the fundamentals of competing risks in survival analysis with this curated playlist of scholarly articles. Featured authors include Thomas A. Louis (Johns Hopkins Bloomberg School of Public Health) and Daniel Scharfstein (Johns Hopkins Bloomberg School of Public Health), offering expert insights into statistical methods and practical applications. Dive into Part 1 for a clear introduction and essential concepts.