Abstract
Bodhini Jayasuriya and Richard Valliant
(1995) "An Application Of Regression And Calibration
Estimation To Post-Stratification In A Household Survey," Proceedings
of the Section on Survey Research Methods, American Statistical
Association.
This paper empirically compares three estimation
methods—regression, calibration, and principal person—used
in a household survey for post-stratification.
Post-stratification is important in many household surveys to
adjust for nonresponse and the population undercount that
results from frame deficiencies. The correction for
population undercoverage is usually achieved by adjusting
estimated people counts in each post-stratum to equal the
corresponding population control counts typically available
from an external source such as a census. We will compare
estimated means from the three methods and their estimated
standard errors for a number of expenditures from the
Consumer Expenditure Survey sponsored by the Bureau of Labor
Statistics in an attempt at understanding how each estimation
method accomplishes this step in post-stratification.
Last Modified Date: July 19, 2008
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