A semiparametric Cox proportional hazards regression model is commonly used to analyze uncensored and right-censored event-time data. The new estimation command stintcox fits the Cox model to interval-censored event-time data.
Interval-censoring occurs when the time to an event of interest, such as recurrence of cancer, is not directly observed but is known to lie within an interval. For example, the recurrence of cancer can be detected between periodic examinations, but the exact time of recurrence cannot be observed. We know only that cancer recurred sometime between the previous and current examinations. Ignoring interval-censoring may lead to incorrect (biased) results.
Semiparametric estimation, when the baseline hazard function is left completely unspecified, of interval-censored event-time data is challenging because none of the event times are observed exactly. As such, "semiparametric" modeling of these data often resorted to using spline methods or piecewise-exponential models for the baseline hazard function. Genuine semiparametric modeling of interval-censored event-time data was not available until recent methodological advances, which are implemented in the stintcox command.