Casual Inference for Complex Observational Data - October 29

The Columbia Population Research Center's Computing and Methods Core 

is pleased to invite you to: 

"Casual Inference for Complex Observational Data"

presented by

Chuck Huber, PhD

Associate Director of Statistical Outreach

StataCorp LLC

Adjunct Associate Professor of Biostatistics

Texas A&M School of Public Health 

 

RSVP REQUIRED

https://cupop.formstack.com/forms/stataseminar

 

WHEN & WHERE Monday, October 29, 2018 Room 1109, 1255 Amsterdam (between 121 & 122)

 

ABSTRACT Observational data often have issues which present challenges for the data analyst.  The treatment status or exposure of interest is often not assigned randomly.  Data are sometimes missing not at random (MNAR) which can lead to sample selection bias.  And many statistical models for these data must account for unobserved confounding.  This talk will demonstrate how to use standard maximum likelihood estimation to fit extended regression models (ERMs) that deal with all of these common issues alone or simultaneously.

 

ABOUT THE PRESENTER Chuck Huber is Associate Director of Statistical Outreach at StataCorp and Adjunct Associate Professor of Biostatistics at the Texas A&M School of Public Health. In addition to working with Stata's team of software developers, he produces instructional videos for the Stata Youtube channel, writes blog entries, develops online NetCourses and gives talks about Stata at conferences and universities.  Most of his current work is focused on statistical methods used by behavioral and health scientists. He has published in the areas of neurology, human and animal genetics, alcohol and drug abuse prevention, nutrition and birth defects. Dr. Huber currently teaches introductory biostatistics at Texas A&M where he previously taught categorical data analysis, survey data analysis, and statistical genetics.

 

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