Seminar Notice
                        Statistics Laboratory
                         Iowa State University


Date and Time:  Thursday, February 5, 1998, 11:00a.m.

Place:   1116 Sweeney

Speaker: Gauri S. Datta, 
         Department of Statistics
         University of Georgia
         U.S. Bureau of Labor Statistics
         and
         U.S. Bureau of the Census 

Title:   Approximations to Mean Squared Errors of Estimated Best Linear
         Unbiased Predictors in Small Area Estimation with An Application 
         to Median Income for the U.S. States 


                             Abstract:
  
There is a growing demand by many U.S. and other government agencies 
to produce reliable statistics for various subgroups of a population.
It is now widely recognized that direct survey estimates for these
subgroups are likely to yield unacceptably large standard errors 
since only a few samples for the subgroups can be obtained from the
surveys.  The problem is generally referred to as a small area
estimation.  Model based inference is gaining popularity in small
area estimation since it can effectively use information from
various sources in conjuction with the survey data.  In this talk, 
we consider second order accurate approximations to the mean squared
errors of estimated best linear unbiased predictors (EBLUP) of mixed effects
in a normal mixed linear setup.  This setup covers many important
small area models including Fay-Herriot model and the nested error 
regression model of Battese, Harter and Fuller (BHF) (1988).  We
extend BHF, Kackar-Harville and Prasad-Rao approximations to MSE of
EBLUP when variance components are estimated by maximum likelihood and
residual maximum likelihood methods.  As an alternative to estimated
MSE based on Prasad-Rao-type approximations, we propose, following
Laird and Loius (1987) and Butar and Lahiri (1997), a bootstrap
approximation to the estimated 
MSE.  This result is similar in spirit to the work of Fuller (1989).
A naive bootstrap in an unbalanced Fay-Herriot model fails to account
for the bias in variance estimation.  
  
We demonstrate the effectiveness of our procedure in estimating the
median income of four-person families for all the U.S. states and the
District of Columbia.

Coffee:  10:45 a.m., 104 Snedecor

Seminar schedules and abstracts are available via WWW:
   http://www.stat.iastate.edu