Authors

• Helge Toutenburg
• Christian Heumann
• Thomas Nittner
• Sandro Scheid

Abstract

This paper gives a detailed overview of the problem of missing data in parametric and nonparametric regression. Theoretical basics, properties as well as simulation results may help the reader to get familiar with the common problem of incomplete data sets. Of course, not all occurences can be discussed so this paper could be seen as an introduction to missing data within regression analysis and as an extension to the early paper of [19.

Keywords

• Generalized additive models
• imputation
• missing data mechanism
• MSE–superiority
• Regression Analysis