Do you have event-time data that you would like to model, but you’re unsure exactly when the events occurred?
In survival analysis, interval-censored event-time data arise when the event of interest is not always observed exactly but is known to have occurred within a specific time interval. Stata 17 introduced the stintcox command to fit genuine semiparametric Cox models for such data, and Stata 18 expanded its capabilities by adding support for time-varying covariates (TVCs). Building on this, Stata 19 introduces the new stmgintcox command, enabling the modeling of interval-censored multiple-event data while accounting for potential correlations between event times across different event types.
In this webinar, we will describe the fundamental types of interval-censored data and demonstrate how to fit the semiparametric Cox proportional-hazards model using the stintcox command. We will provide examples using both single-record and multiple-record-per-subject datasets and show how to incorporate TVCs. Additionally, we will discuss how to interpret and plot results and how to assess the proportional hazards assumption. Finally, we will show you how to fit a marginal Cox proportional-hazards model to interval-censored multiple-event data and perform a more powerful test for common covariate effects across all events.
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 with instructions on how to access the webinar.
Registration deadline: 5 July 2026. Registration
