Abstract #300970


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JSM 2002 Abstract #300970
Activity Number: 285
Type: Contributed
Date/Time: Wednesday, August 14, 2002 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract - #300970
Title: On the Regression Calibration in Measurement Error Models
Author(s): Chi-Lun Cheng*+ and John Van Ness
Affiliation(s): Academia Sinica and University of Texas, Dallas
Address: , Taipei, , 115, Taiwan, R.O.C.
Keywords: measurement error model ; regression calibration
Abstract:

This paper discusses the point estimation of the unknown parameters in linear and nonlinear measurement error (errors-in-variables) models. The estimation approach used is the regression calibration (RC) method. Generally speaking, RC is only an approximation method, which will not result in a consistent estimator. However, in some special cases, such as the linear measurement error model, it gives a consistent estimator. Although RC has been implicitly or explicitly used by many authors, its name and a more detailed discussion was first found in Carroll, Ruppert and Stefanski (1995, chapter 3). This paper reviews some recent approaches due to Gleser (1997) and Lee (1995), as well as some recent suggestions are presented.


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