A method to correct for frame membership error in dual frame estimators

Articles and reports: 12-001-X201900300008

Description:

Dual frame surveys are useful when no single frame with adequate coverage exists. However estimators from dual frame designs require knowledge of the frame memberships of each sampled unit. When this information is not available from the frame itself, it is often collected from the respondent. When respondents provide incorrect membership information, the resulting estimators of means or totals can be biased. A method for reducing this bias, using accurate membership information obtained about a subsample of respondents, is proposed. The properties of the new estimator are examined and compared to alternative estimators. The proposed estimator is applied to the data from the motivating example, which was a recreational angler survey, using an address frame and an incomplete fishing license frame.

Issue Number: 2019003
Author(s): Lin, Dong; Liu, Zhaoce; Stokes, Lynne

Main Product: Survey Methodology

FormatRelease dateMore information
HTMLDecember 17, 2019
PDFDecember 17, 2019

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