DEPARTMENT OF STATISTICS
Statistics Colloquium
University of Connecticut
Storrs, Connecticut
The Department of Statistics Cordially invites you to a Colloquium
Abidemi Adeniji
Boehringer Ingelheim
Incorporating Diagnostic Accuracy into the Estimation of
Discrete Survival Function with Lost-to-follow-up
ABSTRACT
The product limit or Kaplan-Meier (KM) estimator is commonly used to estimate the
survival function in the presence of incomplete time to event. Application of this method
assumes inherently that the occurrence of an event is known with certainty. However, the
clinical diagnosis of an event is often subject to misclassification due to assay error or
adjudication error, by which the event is assessed with some uncertainty. In the presence
of such errors, the true distribution of the time to first event would not be estimated
accurately using the KM method. We develop a method to estimate the true survival
distribution by incorporating negative predictive values (NPV) and positive predictive
values (PPV), into a Kaplan-Meier-like method of estimation. This allows us to quantify
the bias in the KM survival estimates due to the presence of misclassified events in the
observed data. We present an unbiased estimator of the true survival function and its
variance. Asymptotic properties of the proposed estimators are provided and these
properties are examined through simulations. We demonstrate our methods using data
from the VIRAHEP-C study.
DATE: Wednesday, February 4, 2015
TIME: 4:00 p.m.
PLACE: Philip E. Austin Building – Room 105
Coffee will be served at 3:30 in room 326