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Missing Data

December 17 2020

Likely biased but possibly useful: the implications of conditioning on future events for interpretation of effects in perinatal epidemiology

Suzanne Bevan 2020 - Virtual Conference Causal Inference, Competing Risks, Confounding, DAGs, Generalizability, Immortal Time Bias, Misclassification, Missing Data, Pediatric, Perinatal, Reproductive, Selection Bias, Women's Health

Session Chairs: Mollie Wood, Dominique Heinke

November 1 2019

An Introduction to Quantitative Bias Analysis

Suzanne Bevan SERtalks, Video, Webinar Confounding, Missing Data, Quantitative Bias Analysis, Selection Bias, Simulation

Richard MacLehose, University of Minnesota

October 16 2019

Assessment of recording bias in pregnancy studies using health care databases: An application to neurologic conditions.

Suzanne Bevan SERjournal, SPC Event, Video, Webinar Big Data, Confounding, Generalizability, Misclassification, Missing Data, Neurology, Perinatal, Reproductive

Sarah McDonald, IQVIA LINK TO ARTICLE

June 21 2019

The Baddest of the Bad: Ranking the Most Pernicious Biases Facing Observational Studies

Suzanne Bevan 2019, Annual Meeting Recording, Video Causal Inference, Collider Bias, Confounding, DAGs, External Validity, Generalizability, Immortal Time Bias, Information bias, Mathematical Modeling, Misclassification, Missing Data, Selection Bias, Survivor Bias

March 13 2019

Application of propensity scores and inverse probability weighting for estimating policy-relevant effects in epidemiology

Suzanne Bevan SERdigital, Video, Webinar Causal Inference, Cohort, Confounding, External Validity, HIV/STI, Inverse Probability Weight, Mental Health, Methods/Statistics, Missing Data, P-Values, Propensity Score, Randomized Controlled Trial, Selection Bias, Statistics (e.g. Hypothesis Testing), Transportability

June 22 2018

Thinking Beyond Diagnosis, Procedure, and Drug Codes: Shaping the Future of Epidemiologic Research Using Electronic Healthcare Databases

Suzanne Bevan 2018, Annual Meeting Recording, Video Cohort, Confounding, Machine Learning, Missing Data, Selection Bias

November 10 2017

Representative sampling is overrated. AGREE OR DISAGREE?

Suzanne Bevan SERdigital, Video, Webinar Cancer, Generalizability, Genetics, Methods/Statistics, Missing Data, Natural Disasters, Representativeness, Validation Studies

November 16 2016

Perspective of relative versus absolute effect measures

Suzanne Bevan SERdigital, Video, Webinar Bayes, Case-Control, Infectious Disease, Inverse Probability Weight, Missing Data, P-Values, Perinatal, Social Media, Statistics (e.g. Hypothesis Testing), Surveillance

Charles Poole, UNC Chapel Hill Donna Spiegelman, Harvard University

November 4 2015

Big Data: What it Means for Epidemiology

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

June 1 2015

2015 Keynote Cassel Lecture: “The Scientific Approach to Causal Inference”

Suzanne Bevan 2015, Annual Meeting Recording, Video Causal Inference, Confounding, DAGs, External Validity, Mediation, Methods/Statistics, Missing Data, Randomized Controlled Trial, Selection Bias, Transportability

Judea Pearl Articles relevant to this video: 1. Causal inference from big data http://ftp.cs.ucla.edu/pub/stat_ser/r450.pdf 2. Generalizing Experimental Findings http://ftp.cs.ucla.edu/pub/stat_ser/r452.pdf

Society for Epidemiologic Research

Contact:

Suzanne Bevan
Executive Director
PO Box 1831
Eagle, Idaho 83616
sbevan@epiresearch.org

@societyforepi

#SERmember spotlight on #epidemiologist and professor @HarvardChanSPH Nancy Krieger! Her research includes #socialepi #healthequity and #womenshealth. Learn more on her Wikipedia page https://t.co/m77ufiV9cJ #epidemiology #WomenInSTEM

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@societyforepi

@AmJEpi: New in AJE: @navdep_kaur & colleagues found worsening internalizing symptoms in US adolescents. Lack of sleep partially explains increased loneliness. @epi_kerrykeyes @AvaDHamilton @chen_qixuan @DeborahHasin @Magda_Cerda @ssm2183 Read more: https://t.co/IyZU470Hte

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@societyforepi

👂Check out the latest episode of SERious epi with @Lizstuartdc! https://t.co/MVWfRoHSXS

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