Abstract #301329

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JSM 2002 Abstract #301329
Activity Number: 16
Type: Contributed
Date/Time: Sunday, August 11, 2002 : 2:00 PM to 3:50 PM
Sponsor: Section on Survey Research Methods*
Abstract - #301329
Title: Linearization Variance Estimators for Survey Data with Missing Responses
Author(s): A. Demnati*+ and J. N. Rao
Affiliation(s): Statistics Canada and Carleton University
Address: Tunney's Pasture, R.H.C. Bldg, 15 Floor, Ottawa, Ontario, K1A 0T6, Canada
Keywords: Item nonresponse ; random imputation ; Taylor linearization ; unit nonresponse ; weighting adjustment.
Abstract:

Demnati and Rao (2001) considered variance estimation for survey data and proposed a new method that leads to a unique linearization variance estimator with desirable properties. The estimators can be defined either implicitly or explicitly as solutions of estimation equations using survey weights or calibration weights. We extend our work to deal with missing data problem. This paper shows how to get valid variance estimates under a variety of methods for dealing with missing data, covering weighting adjustment, which is often used to compensate for complete non-response, as well as imputation, which is often used to produce a complete data set.

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Revised March 2002