Estimation of Linear Regression Models with Missingness of Observations on Both the Explanatory and Study Variables-Part I: Theoretical Results

Toutenburg, Helge; Srivastava, V. K. (2000): Estimation of Linear Regression Models with Missingness of Observations on Both the Explanatory and Study Variables-Part I: Theoretical Results. Collaborative Research Center 386, Discussion Paper 184

Abstract

This paper discusses the estimation of coefficients in a linear regression model when there are some missing observations on an explanatory variable and the study variable individually as well as simultaneously. The first order regression method of imputation is followed and the least squares procedure is applied. Efficiency properties of estimators are then investigated employing the large sample asymptotic theory.

• Item Type: Paper (Research Paper)
• Faculties: Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386; Special Research Fields > Special Research Field 386
• Subjects: 500 Science > 510 Mathematics
• Language: English