Using diagnostic measures to detect non-MCAR processes in linear regression models with missing covariates

Toutenburg, Helge and Fieger, A. (2000): Using diagnostic measures to detect non-MCAR processes in linear regression models with missing covariates. Collaborative Research Center 386, Discussion Paper 204

Abstract

This paper presents methods to analyze and detect non-MCAR processes that lead to missing covariate values in linear regression models. First, the data situation and the problem is sketched. The next section provides an overview of the methods that deal with missing covariate values. The idea of using outlier methods to detect non-MCAR processes is described in section 3. Section 4 uses these ideas to introduce a graphical method to visualize the problem. Possible extensions conclude the presentation.

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