There is an upcoming live webinar, that is free and open to the public:
Lessons from COVID-19: Non-random Missing Data and Its Consequences
DATE: Tuesday, Aug 8, 2023
TIME: 12pm ET (16:00 UTC)
WHERE: online (BigMarker is a browser based platform, no download required, use Chrome for best experience)
SIGN-UP: on Meetup
COST: Free
DESCRIPTION:
A fundamental challenge for survey and observational datasets is that not all records in the dataset are complete; key pieces of information may be missing.
In this talk I work through the models and methods from the paper
MODELING RACIAL/ETHNIC DIFFERENCES IN COVID-19 INCIDENCE WITH COVARIATES SUBJECT TO NON-RANDOM MISSINGNESS
They write:
In emergency situations, such as a surging pandemic, it is easy to see how the disease process itself may induce non-random missingness of covariates. For example, during a period of rapidly increasing caseloads, such as the Delta and Omicron surges of the COVID-19 pandemic, the overwhelming number of cases is likely to limit the ability of case investigators to collect data that are as detailed as those collected during lower-incidence periods. These differences may also be more pronounced when comparing wealthier and poorer jurisdictions with differential resources for case-finding and intervention.
Using the Stan language and CmdStanR interface, together with a simulated dataset of COVID-19 cases and population demographics, where age, gender, race/ethnicity, and neighborhood have varying degrees of missingness, we will demonstrate how different approaches produce different estimates of COVID-19 prevalence among key demographics.
Co-promotion
This event is being co-promoted with R-Ladies NYC. R-Ladies NYC is part of a world-wide organization to promote gender diversity in the R community. We aspire to encourage and support women and gender minorities interested in learning and sharing their experiences in R programming by hosting a variety of events including talks, workshops, book clubs, data dives, and socials. (https://www.rladiesnyc.org/)
SPEAKER
Mitzi Morris is a member of the Stan Development Team and serves on the Stan Governing Body. Since 2017 she has been a full-time Stan developer, working for Professor Andrew Gelman at Columbia University, where she has contributed to the core Stan C++ platform and developed CmdStanPy, a modern Python interface for Stan. She is also as an active Stan user, developing, publishing, and presenting on Bayesian models for disease mapping. Prior to that she has worked as a software engineer in both academia and industry, working on natural language processing and search applications as well as data analysis pipelines for genomics and bioinformatics.
Mitzi on GitHub github.com/mitzimorris
Video Recording
This event will be recorded and placed on our YouTube. We usually have it up within 24 hours of the event. Subscribe to our YouTube and set your notifications:
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