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

Programming with hierarchical statistical models:
An introduction to the BUGS-compatible NIMBLE system for MCMC and more

Friday, April 13, 2018
11:00 am – 1:00 pm Eastern

Presenter:
Chris Paciorek
Adjunct Professor, Statistical Computing Consultant
Department of Statistics
University of California, Berkeley

Description:
This webinar will introduce attendees to the NIMBLE system for programming with hierarchical models in R. NIMBLE
(r-nimble.org) is a system for flexible programming and dissemination of algorithms that builds on the BUGS language for declaring hierarchical models. NIMBLE provides analysts with a flexible system for using MCMC, sequential Monte Carlo and other techniques on user-specified models. It provides developers and methodologists with the ability to write algorithms in an R-like syntax that can be easily disseminated to users. C++ versions of models and algorithms are created for speed, but these are manipulated from R without any need for analysts or algorithm developers to program in C++.

While analysts can use NIMBLE as a drop-in replacement for WinBUGS or JAGS, NIMBLE provides greatly enhanced functionality in a number of ways. The webinar will first show how to specify a hierarchical statistical model using BUGS syntax (including user-defined function and distributions) and fit that model using MCMC (including user customization for better performance). We will demonstrate the use of NIMBLE for biostatistical methods such as semiparametric random effects models and clustering models. We will close with a discussion of how to use the system to write algorithms for use with hierarchical models, including building and disseminating your own methods.

Click Here to Register (April 13)
Must Register before April 12. Instructions for access will be e-mailed to all participants on April 12.

Sensitivity analysis in observational research: introducing the E-value

Friday, September 28, 2018
10:00 am – 12:00 pm Eastern

Presenter:
Dr. Tyler VanderWeele
Professor of Epidemiology
Harvard School of Public Health

Abstract:
Sensitivity analysis is useful in assessing how robust an association is to potential unmeasured or uncontrolled confounding. This webinar introduces a new measure called the "E-value," which is related to the evidence for causality in observational studies that are potentially subject to confounding. The E-value is defined as the minimum strength of association, on the risk ratio scale, that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment–outcome association, conditional on the measured covariates. A large E-value implies that considerable unmeasured confounding would be needed to explain away an effect estimate. A small E-value implies little unmeasured confounding would be needed to explain away an effect estimate. The speaker and his collaborators propose that in all observational studies intended to produce evidence for causality, the E-value be reported or some other sensitivity analysis be used. They suggest calculating the E-value for both the observed association estimate (after adjustments for measured confounders) and the limit of the confidence interval closest to the null. If this were to become standard practice, the ability of the scientific community to assess evidence from observational studies would improve considerably, and ultimately, science would be strengthened.

Reference: VanderWeele, T.J. and Ding, P. (2017). Sensitivity analysis in observational research: introducing the E-value. Annals of Internal Medicine, 167:268-274.
Online E-value Calculator: https://mmathur.shinyapps.io/evalue/

Click Here to Register (Sept 28)
Must register before September 27. Instructions for access will be e-mailed to all participants on September 27.

Biostatistical Methods for Wearable and Implantable Technology

Friday, October 26, 2018
10:00 am – 12:00 pm Eastern

Presenter:
Dr. Ciprian Crainiceanu
Professor, Department of Biostatistics
Johns Hopkins University

Abstract:
Wearable and Implantable Technology (WIT) is rapidly changing the Biostatistics data analytic landscape due to their reduced bias and measurement error as well as to the sheer size and complexity of the signals. In this talk I will review some of the most used and useful sensors in Health Sciences and the ever expanding WIT analytic environment. I will describe the use of WIT sensors including accelerometers, heart monitors, glucose monitors and their combination with ecological momentary assessment (EMA). This rapidly expanding data eco-system is characterized by multivariate densely sampled time series with complex and highly non-stationary structures. I will introduce an array of scientific problems that can be answered using WIT and I will describe methods designed to analyze the WIT data from the micro- (sub-second-level) to the macro-scale (minute-, hour- or day-level) data.

Click Here to Register (Oct. 26)
Must register before October 25. Instructions for access will be e-mailed to all participants on October 25.

Lessons and Strategies for a Career in Academia: A Conversation

Friday, December 14, 2018
10:00 am – 12:00 pm Eastern

Presenter:
Dr. Leslie McClure
Professor & Chair, Department of Epidemiology and Biostatistics
Dornsife School of Public Health at Drexel University

Dr. Elizabeth Stuart
Associate Dean for Education and Professor of Biostatistics, Mental Health, and Health Policy and Management
Johns Hopkins Bloomberg School of Public Health

Abstract:
As a Biostatistician, there are many paths to a successful career. Each has benefits and drawbacks and will depend on an individual’s own skills and preferences. In this webinar, Drs. Elizabeth Stuart and Leslie McClure will host a conversation about their academic careers, including providing some strategies for success and describing some of the challenges they've faced. They'll consider important questions, such as: What to look for in a job? How to develop meaningful collaborations (and get out of those that are not productive)? How to prioritize activities with an eye towards promotion (e.g., collaborative and methodological projects)? How to balance teaching, research, and grant requirements? And how to balance all of that with things outside of work? However, the exact direction of the conversation will depend on the questions and engagement from webinar participants.

Registration coming soon!

Previous Webinars & Recordings

 

Please contact Michael Hudgens if you have topic suggestions for future webinars.