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Webinar: Analyzing interval-censored survival-time data in Stata

Overview

When: January 24, 2018 at 10:00 AM CT
Duration: 1 hour
Where: Join us from anywhere!
Cost: Free—but registrations are limited

In survival analysis, right-censored data have been studied extensively and can be analyzed using Stata's comprehensive suite of survival commands, including commands such as streg for fitting parametric survival models. However, not all survival data are right-censored. Right-censored data are a special case of interval-censored data. Interval-censoring occurs when the failure time of interest is not exactly observed but is only known to lie within some interval. Left-censoring, which occurs when the failure is known to happen sometime before the observed time, is also a special case of interval-censoring. Survival data may contain a mixture of uncensored, right-censored, left-censored, and interval-censored observations.

Join Xiao Yang, Senior Statistician and Software Developer, as she describes basic types of interval-censored data and demonstrates how to fit parametric survival models to these data using Stata's new stintreg command. She will also discuss how to interpret and plot results and how to graphically evaluate goodness of fit.

How to join

The webinar is free, but you must register to attend. Registrations are limited so register soon.

We will send you an email prior to the start of the course with instructions on how to access the webinar. You will need access to Adobe Connect to attend.

Don't miss this opportunity.

Register

Registration is now closed.

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Presenter: Xiao Yang

Xiao Yang portrait

Xiao Yang is a Senior Statistician and Software Developer at StataCorp LLC and is the primary developer of Stata's new survival analysis features for interval-censored data. She has a bachelor's degree in computer science from the University of Electronic Science and Technology of China, a master's degree in mathematics from Southeast Missouri State University, and a master's degree in statistics from the University of Iowa. Her research interests lie in biostatistics and Bayesian analysis.


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