Abstract #300712

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JSM 2003 Abstract #300712
Activity Number: 234
Type: Topic Contributed
Date/Time: Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Survey Research Methods
Abstract - #300712
Title: Jackknife Variance Estimation for Two-Phase Sampling in the National Resources Inventory
Author(s): Jean D. Opsomer*+ and Wayne A. Fuller and Xiaoxi Li
Companies: Iowa State University and Iowa State University and Iowa State University
Address: Dept. of Statistics, Ames, IA, 50011-0001,
Keywords: regression estimation ; natural resource survey ; replication variance estimation
Abstract:

The National Resources Inventory (NRI), conducted annually since 2000 by the Natural Resources Conservation Service of the U.S. Department of Agriculture, relies on a complex two-phase design. Estimation procedures used to create a public release dataset incorporate several population controls, as well as a number of phase one estimates. Controlling to population and phase one variables is achieved through raking and regression procedures. Analytically derived variance estimators are impractical in this context, because fully accounting for the variability of the estimates requires access to the phase one data, while only the phase two data are provided in the public release files. Fuller (1998) proposed replication variance estimation as a way to incorporate the variance of phase one controls into the two-phase estimation procedure. A jackknife variance estimation procedure partly based on this approach is proposed in the talk. We describe the theoretical properties and the practical behavior of the procedure.

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