Short course

SC2 | Semiparametric regression analysis of interval-censored data

Instructors: Danyu Lin, The University of North Carolina at Chapel Hill; Donglin Zeng, University of Michigan; and Yulia Marchenko, StataCorp

Date: Sunday, 23 March 2025

Time: 8:00 a.m.–5:00 p.m. CT

Fee: $265 to $475

In clinical and epidemiological studies, the onset of an asymptomatic disease (e.g., diabetes, hypertension, chronic obstructive pulmonary disease, HIV infection, SARS-CoV-2 infection, cancer, or dementia) cannot be observed directly but rather is known to occur sometime between two consecutive clinical examinations. The two examinations bookend a time interval, such that the event time is “interval-censored.” It is highly challenging to analyze interval-censored data because none of the event times is exactly known; therefore, investigators have resorted to statistical methods that are unreliable or even invalid. Recent theoretical and numerical advances, as well as software implementation in R, SAS, and Stata, have made semiparametric regression analysis of interval-censored data a practical reality. The goal of this short course is to present these recent developments to a broad audience in an accessible manner. [Read more ...]

Yulia Marchenko

Vice President, Statistics and Data Science

Yulia Marchenko is Vice President, Statistics and Data Science at StataCorp. Yulia has been with Stata for over 20 years and has more than 25 years of software development experience. Her primary responsibility is to oversee Stata's scientific software development. Her areas of interest include Bayesian analysis, multiple imputation, meta-analysis, multilevel modeling, survival analysis, power analysis, causal analysis, and other areas of statistics, biostatistics, and econometrics. Yulia has a PhD in statistics from Texas A&M University.