JSM 2005 - Toronto

Abstract #303602

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 59
Type: Topic Contributed
Date/Time: Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor: Social Statistics Section
Abstract - #303602
Title: Estimating Variance in Highly Clustered Survey Samples
Author(s): Jiahe Qian*+
Companies: Educational Testing Service
Address: Rosedale Road MS02T, Princeton, NJ, 08541, United States
Keywords: clustering effects ; delete-d jackknife approach ; Winsorized estimates ; truncated estimates
Abstract:

The highly clustered groups in survey samples may have a striking impact on estimates and, therefore, contribute excessively to variance estimates. Such impacts often are found in the jackknifed variance estimates in analyzing data of the National Assessment of Educational Progress (NAEP). I propose a delete-d jackknife approach to smooth the influence of clusters on variance estimation without introducing bias into variance estimates. This study applies the approach to the 2003 NAEP reading assessment samples. I also compare the delete-d jackknifed estimates with the Winsorized and truncated estimates.

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Revised March 2005