PLACE: 319 Snedecor

SPEAKER: Professor Hal Stern, Department of Statistics, Iowa State University

TITLE:  Inference for Extremes with An Application to Disease Mapping
 

ABSTRACT:

Hierarchical probability models are commonly used to estimate small-area
disease-morbidity or disease-mortality rates. From the resulting estimates
it is often desirable to identify small areas (e.g., counties) with
unusually high or low disease risk after accounting for known risk factors.
Traditional estimates of the unexplained risk are based on the
squared-error loss function; such estimates have good ensemble properties
but may be suboptimal for some features of the distribution of risk
parameters.  We explore the use of alternative loss functions to derive
improved estimates of extreme values.  A disease mapping application
is used to illustrate the approach.  A simulation study is used to compare
the different loss functions.

COFFEE: 3:45 p.m., 104 Snedecor Hall