Zero-inflated modelling for characterizing coverage errors of extracts from the US Census Bureau's Master Address File

To meet the strategic goals and objectives for the 2020 census, the US Census Bureau must make fundamental changes to the design, implementation and management of the decennial census. The changes must build on the successes and address the challenges of the previous censuses. Of particular interest...

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Bibliographic Details
Published in:Journal of the Royal Statistical Society. Series A, Statistics in society Statistics in society, 2017-01, Vol.180 (1), p.73-97
Main Authors: Young, Derek S., Raim, Andrew M., Johnson, Nancy R.
Format: Article
Language:English
Subjects:
Census
Census of Population
Censuses
Computer simulation
Coverage
Cross‐validation
Errors
Gages
Gauges
Geography
Government agencies
Housing
Mathematical models
Modelling
Negative binomial
Regression
Sample survey frame improvement
Statistical analysis
Statistics
Variable selection
Zero‐inflated counts
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Summary:To meet the strategic goals and objectives for the 2020 census, the US Census Bureau must make fundamental changes to the design, implementation and management of the decennial census. The changes must build on the successes and address the challenges of the previous censuses. Of particular interest is to gauge the on-going quality of the census frames. We address this topic by discussing a set of statistical models for the Master Address File that will produce estimates of coverage error at levels of geography down to the block level. The distributions of added and deleted housing units in a block are used to characterize the undercoverage and overcoverage respectively. The data used are from the 2010 address canvassing operation. As will be shown, these distributions are highly right skewed with a very large proportion of 0 counts. Hence, we utilize zero-inflated regression modelling to determine the predicted distribution of additions and deletions. In addition to standard statistical measures, we gauge the performance of this model by simulating a 2010 address canvassing operation using a specified coverage level. We also discuss future maintenance and updating of this model.
ISSN:0964-1998
1467-985X
DOI:10.1111/rssa.12183