Edsel Peña
Department of Statistics
University of South Carolina
Goodness-of-Fit Tests with Right-Censored Data
The use of intensity processes or hazard functions is a natural and
convenient way of specifying failure-time models arising in engineering and
reliability life-testing studies, medical or clinical trials, actuarial
settings, and in economic situations. It is typical in such studies, where
the primary outcome variable is the time to occurrence of an event, to have
data with truncated and/or censored observations. Two problems of interest
in these situations are to develop goodness-of-fit procedures and to develop
methods for validating the assumed model. In this talk I will describe a
general approach in constructing a class of goodness-of-fit tests for these
intensity or hazard-based models in the presence of incomplete data. The
resulting procedures possess optimality properties and includes as special
cases generalizations of tests used with complete data, in particular, a
generalization of Pearson's classical chi-square test. The test statistics
depend on generalized residuals, and the theoretical developments of the
procedures reveal certain properties of these residuals. The results shed
light on the validity of existing and ad hoc model validation methods based
on these generalized residuals.
Back to Colloquium Series