SPEAKER:
Michael Elliot
Department of
Biostatistics and Epidemiology,
University of Pennsylvania, School of Medicine
TITLE:
A Bayesian Approach to 2000 Census Evaluation Using A.C.E. Survey
Data and Demographic Analysis
ABSTRACT:
| Demographic analysis of
data on births, deaths and migration, together with coverage measurement
surveys that use capture-recapture methods, have established that U.S.
Census counts may be flawed for groups such as young and middle-aged
African-American men. Previous work using 1990 Census data in
African-Americans 30-49 proposed a hierarchical Bayesian model that
assembled Census, follow-up survey, and demographic data, providing a
principled solution to the problem of negative estimated counts in some
subpopulations, smoothing highly variable estimates across subpopulations,
and providing estimates of precision that incorporate uncertainty in the
demographic analysis estimates. Here we extend that effort by
refining the hierarchical model design, expanding the set of models
considered, considering the presence of bias in the Census or follow-up
survey counts, obtaining Bayes factors for use in model selection and
model averaging, and applying the methods to the entire 2000 U.S. Census.
Comparisons with the 1990 U.S. Census results are included as well. |
REFRESHMENTS: 10:45
am; 104 Snedecor Hall