STATISTICS COLLOQUIUM
Jianguo Sun
Professor of Statistics
University of Missouri
Sieve Maximum Likelihood Regression Analysis of Bivariate Interval-censored Failure Time Data
ABSTRACT
Interval-censored failure time data arise in a number of fields and many authors have discussed various issues related to their analysis. However, most of the existing methods are for univariate data and there exists only limited research on bivariate data, especially on regression analysis of
bivariate interval-censored data. In this talk, we will discuss a class of semiparametric transformation models for the problem and for inference, a sieve maximum likelihood approach will be developed. The model provides a great flexibility, in particular including the commonly used proportional hazards model as a special case, and in the approach, Bernstein polynomials
are employed. An illustrative example will also be discussed.
DATE: Wednesday, April 27, 2016
TIME: 4:00 pm – 5:00 pm
PLACE: Philip E. Austin Bldg., Rm. 105
Coffee will be served at 3:30 in the Noether Lounge (AUST 326)
For more information, contact: TracyBurke at tracy.burke@uconn.edu