Abstract #300735


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JSM 2002 Abstract #300735
Activity Number: 405
Type: Contributed
Date/Time: Thursday, August 15, 2002 : 10:30 AM to 12:20 PM
Sponsor: Section on Survey Research Methods*
Abstract - #300735
Title: Evaluation of Inferential Performance Through Confidence Bounds for Power Curves
Author(s): Amang Sukasih*+ and John Eltinge
Affiliation(s): Mathematica Policy Research, Inc. and U.S. Bureau of Labor Statistics
Address: 600 Maryland Ave., SW, Suite 550, Washington, District of Columbia, 20024-2512, USA
Keywords: Complex Survey ; Design Based Inference ; Efficiency ; Generalized Least Squares ; Hypothesis Testing ; U.S. Consumer Expenditure Survey
Abstract:

In the analysis of complex survey data, one often uses a nominal pivotal quantity in a test of the null hypothesis of a parameter of interest. Due to limitations of the sample design, the data collection process or proposed estimation methods, test procedures based on this pivotal quantity may be affected by: 1.) bias of the point estimators; 2.) inflation in the variance of the point estimator; and 3.) bias of the variance estimator. This paper presents some methods to evaluate the relative magnitudes of the effects of 1.)-3.) on the power curve of the associated test. Special emphasis is placed on the construction of confidence bounds for this power curve.

The methods are applied to data from the U.S. Consumer Expenditure Survey, which collects data through two instruments known as the diary and the interview. For 78 expenditure items, data are collected through both the diary and interview but, currently, published estimates are based only on the diary data. Prospective methods to combine the diary and interview data sources involve trade-offs between 1.)-3.). Estimated power curves, and associated confidence bounds, provide an empirical assessment of these three factors.


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