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External Validity Improvement for Epidemiologic Analyses (EVIEA)

Improving the External Validity of Estimates from Epidemiologic Analysis Through Innovative Statistical Methods

Health data

For various reasons, cohort studies generally forgo probability sampling required to obtain population representative samples. However, such cohorts lack population representativeness, which invalidates estimates of population prevalence for novel health factors that are only available in cohorts. To improve external validity of estimates from epidemiologic analysis, EVIVA aims to develop innovative statistical methods with applications to a wide range of non-probability samples. For example, Undiagnosed SARS-CoV-2 Seropositivity During the First Six Months of the COVID-19 Pandemic in the United States; US population mortality and prevalences estimation of various diseases from the non‐representative US National Institutes of Health–American Association of Retired Persons cohort; etc.

Please see below for the software development, publications, etc.

Department:Epidemiology and Biostatistics
Room Number:TBD
Director:Yan Li

Office Phone Number:(301) 314-6570
Email:yli6@umd.edu

R package development:PSwtEst_0.1.0.tar.gz

2021

2020