JSM 2005 Online Program

Abstract #304117

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:	132
Type:	Topic Contributed
Date/Time:	Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Survey Research Methods
Abstract - #304117
Title:	A Model Prediction Approach to Measuring Nonsampling Error
Author(s):	Kimberly Henry*+ and Yahia Ahmed
Companies:	U.S. Internal Revenue Service and U.S. Internal Revenue Service
Address:	Statistics of Income Division, Washington, DC, 20013, United States
Keywords:	data quality ; editor judgment error ; net difference rate ; index of inconsistency
Abstract:	Corporate tax returns usually consist of the forms, which contain limited detail reported for tax liability purposes, along with more detailed, yet nonstandardized, supporting documentation. Because data were edited under standards created for statistical purposes, the Statistics of Income Division's editors are placed in a position to make judgments while recording, cleaning, and processing corporate tax return data. Editor judgment error is the largest source of editor-related nonsampling error in the corporate sample. This paper will use model prediction techniques from a subsample of returns selected for quality review to estimate nonsampling error in returns not subject to review. The net difference rate, index of inconsistency, and model adequacy measures will then be computed for the entire sample.

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