Asymptotic Properties of Simple Linear Measurement Error Models

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Atıf İçin Kopyala

DAĞALP R.

COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS, cilt.60, sa.1, ss.71-84, 2011 (ESCI)

• Yayın Türü: Makale / Tam Makale
• Cilt numarası: 60 Sayı: 1
• Basım Tarihi: 2011
• Doi Numarası: 10.1501/commua1_0000000670
• Dergi Adı: COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS
• Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI)
• Sayfa Sayıları: ss.71-84
• Anahtar Kelimeler: Conditional score function, Corrected score function, functional model, generalized linear models, measurement error models, error-free and error-prone predictors, error in variables, M-estimator
• Ankara Üniversitesi Adresli: Hayır

Özet

The main objective of this paper is to study estimators of regression models on the independent variable X which is not directly observed for some reasons. In such a situation, a substitute variable W is observed instead. This substitution complicates the statistical analysis of the observed data when the purpose of the analysis is inference about a model defined in terms of X. The substitution causes a inconsistent estimator; this is defined as a measurement error problem. To correct this problem, the conditional score and corrected score methods are proposed by Stefanski&Carroll (1985) and Nakamura (1990), respectively. In this study, large sample distribution theory for both the conditional score and corrected score estimators are derived and the performance of the estimators and the adequacy of the large sample distribution theory are obtained via Monte Carlo simulation.