ENAR Webinar Series (WebENARs)

As part of ENAR's education initiative, our webinars promote continuing education for professional and student statisticians by disseminating cutting-edge knowledge to our membership. An ENAR webinar (or "webENAR") can strengthen your background in methodology and software, provide an opportunity to learn about a topic outside of your primary area of specialization, or deepen your understanding of an area in which you already work. We invite you to participate and benefit from the expertise of some of North America's leading statisticians and biostatisticians.

The Webinar Committee of the ENAR Regional Advisory Board (RAB) is coordinating this ongoing series of 1- to 2-hour webinars given by renowned experts. Registration fees are by membership category, with a reduced fee for student members. The webinars are planned to be broadly available and we encourage groups at your institution or workplace to participate together. WebENARs provide excellent learning opportunities for students and professionals alike.

WebENAR Registration Fees

Registration fees are determined by membership category.

Schedule of Upcoming Webinars

Entity Resolution with Societal Impacts in Machine Learning

Friday, February 7, 2020
10 a.m. to 12 p.m. Eastern

Presenter:
Rebecca C. Steorts
Assistant Professor, Department of Statistical Science
Duke University

Abstract:
Very often information about social entities is scattered across multiple databases. Combining that information into one database can result in enormous benefits for analysis, resulting in richer and more reliable conclusions. Among the types of questions that have been, and can be, addressed by combining information include: How accurate are census enumerations for minority groups? How many of the elderly are at high risk for sepsis in different parts of the country? How many people were victims of war crimes in recent conflicts in El Salvador? In most practical applications, however, analysts cannot simply link records across databases based on unique identifiers, such as social security numbers, either because they are not a part of some databases or are not available due to privacy concerns. In such cases, analysts need to use methods from statistical and computational science known as entity resolution (record linkage or de-duplication) to proceed with analysis. Entity resolution is not only a crucial task for social science and industrial applications but is a challenging statistical and computational problem itself. In this talk, we describe the past and present challenges with entity resolution, with an application to the El Salvadorian conflict. More specifically, I will discuss unsupervised Bayesian entity resolution models, which are able to identify duplicate records in the data, while quantifying uncertainty. I will highlight the importance of choosing flexible priors and in implementing scalable inference algorithms. I will present preliminary results from the El Salvadorian conflict.

Registration coming soon!


The Role of Statistics in Transforming EHR Data into Knowledge

Friday, May 15, 2020
10 a.m. to 12 p.m. Eastern

Presenter:
Rebecca Hubbard, PhD
Associate Professor of Biostatistics
University of Pennsylvania

Abstract:
The widespread adoption of electronic health records (EHR) as a means of documenting medical care has created a vast resource for research on health conditions, interventions, and outcomes. Informaticians have played a leading role in the process of extracting “real world data” from EHR, with statisticians playing a more peripheral part. However, statistical insights on study design and inference are key to drawing valid conclusions from this messy and incomplete data source. This webinar will describe the basic structure of EHR data, highlight key challenges to research arising from this data structure, and present an overview of some statistical methods that address these challenges. The discussion of issues related to the structure and quality of EHR data will include: data types and methods for extracting variables of interest; sources of missing data; error in covariates and outcomes extracted from EHR and claims data; and data capture considerations such as informative visit processes and medical records coding procedures. The overall goal of this webinar is to illustrate the unique contribution of statistics to the process of generating knowledge from EHR data and equip participants with some tools for doing so.

Registration coming soon!


Previous Webinars & Recordings

 

Please contact Sameera Wijayawardana or Lili Zhao if you have topic suggestions for future webinars.