Suzanne Bevan Methodological Playlists, SERplaylists Cancer, Case-Control, Causal Inference, Confounding, Grants, Methods/Statistics, Misclassification, Molecular, P-Values, Philosophy of Science/Epidemiology, Publishing, Race, Reproductive, Selection Bias, Statistics (e.g. Hypothesis Testing), Survey Sampling, Women's Health 0
Andrew Olshan offers a “random shuffle” of thought-provoking topics in epidemiology. This article features a mix of insights and resources designed to spark discussion and deepen understanding of key concepts in population health research.
Suzanne Bevan 2017, Annual Meeting Recording, Video Causal Inference, Competing Risks, DAGs, Doubly Robust Estimators/TMLE, Global Health, HIV/STI, Machine Learning, Mediation, Methods/Statistics, Misclassification, P-Values, Pediatric, Perinatal, Randomized Controlled Trial, Reproducibility/Transparency, Simulation, Social, Statistics (e.g. Hypothesis Testing)
Suzanne Bevan Applied Playlists, SERplaylists Aging, Causal Inference, Cohort, Competing Risks, Confounding, DAGs, Instrumental Variable, Mendelian Randomization, Methods/Statistics, Misclassification, Neurology, Survivor Bias 0
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.
Suzanne Bevan Methodological Playlists, SERplaylists Bayes, Causal Inference, Cohort, Confounding, Interaction/Effect Measure Modification, Methods/Statistics, Misclassification, P-Values, Quantitative Bias Analysis, Simulation, Statistics (e.g. Hypothesis Testing), Validation Studies 0
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.
Suzanne Bevan SERtalks, Video, Webinar Cardiovascular, Causal Inference, Collider Bias, Confounding, DAGs, Genetics, Instrumental Variable, Mediation, Mental Health, Methods/Statistics, Misclassification, Nutrition/Obesity, Propensity Score, Selection Bias
Maria Glymour, UC San Francisco
Suzanne Bevan SERdigital, Video, Webinar Big Data, Cancer, Causal Inference, Cohort, Confounding, Doubly Robust Estimators/TMLE, HIV/STI, Inverse Probability Weight, Machine Learning, Mediation, Methods/Statistics, Misclassification, Missing Data, Nutrition/Obesity, Philosophy of Science/Epidemiology, Quantitative Bias Analysis, Selection Bias, Simulation
Suzanne Bevan Methodological Playlists, SERplaylists Bayes, Case-Control, Causal Inference, Confounding, External Validity, Methods/Statistics, Misclassification, Quantitative Bias Analysis, Reproductive, Selection Bias, Survey Sampling, Validation Studies 0
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.
Suzanne Bevan SERdigital, Video, Webinar Bayes, Covariate Balance, Inverse Probability Weight, Longitudinal Studies, Methods/Statistics, Misclassification, Nutrition/Obesity, Quantitative Bias Analysis, Quasi-Experimental, Reproductive, Validation Studies
Suzanne Bevan Methodological Playlists, SERplaylists Bayes, Competing Risks, Methods/Statistics, Misclassification 0
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.