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| Duration: | 1 hour |
|---|---|
| Where: | Join us from anywhere! |
| Cost: | Free—but registrations are limited |
Do you have event-time data you would like to model, but you’re not sure exactly when the event occurred?
In survival analysis, interval-censored event-time data occur when the event of interest is not always observed exactly but is known to lie within some time interval. Stata 17 introduced genuine semiparametric Cox models for interval-censored event-time data, and in Stata 18 we have added support for time-varying covariates (TVCs).
In this webinar, we describe basic types of interval-censored data and demonstrate how to fit the semiparametric Cox proportional hazards model to these data using the stintcox command. We will have examples with single-record and multiple-record-per-subject data, and we show how to include TVCs in both. We also discuss how to interpret and plot results and how to assess the proportional-hazards assumption.
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 with instructions on how to access the webinar.
Xiao Yang is a Principal Statistician and Software Developer at StataCorp LLC. Xiao has been developing Stata since 2012. Her interests include survival analysis, longitudinal analysis, Bayesian analysis, and multilevel mixed-effects models. 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.
