JSM 2005 Online Program

Abstract #302611

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	115
Type:	Invited
Date/Time:	Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Government Statistics
Abstract - #302611
Title:	Striving for Data Quality: Pat Doyle's Legacy at the U.S. Census Bureau
Author(s):	Jeffrey Moore*+ and Chester Bowie
Companies:	U.S. Census Bureau and Market Strategies, Inc.
Address:	4700 Silver Hill Rd, stop code #9100, Washington, DC, 20233,
Keywords:	SIPP Methods Panel ; field experiments
Abstract:	Pat Doyle, as anyone who knew her can attest, was a major life force. In eight too-short years as a Census Bureau employee, Pat left her imprint on an astonishingly wide range of projects and activities in the Census Bureau's demographic survey area. This paper discusses Pat's work to improve the quality of the Census Bureau's demographic survey data, focusing particularly on the Survey of Income and Program Participation (SIPP) Methods Panel project. The Methods Panel Project was created to implement a large set of "interview process" improvements in SIPP and to evaluate their success in a series of split-panel field tests. It was largely through Pat's leadership efforts that the Methods Panel project not only survived, but prospered and succeeded. It also was through Pat's insistence that, despite the project's focus on improvements to the interview process, data quality and other user concerns remained preeminent drivers of the research design and the evaluation of instrument changes. The paper describes the Methods Panel Project and its major results, concentrating on Pat's role in bending its agenda toward data quality issues.

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