Missing at Random (MAR) in Nonparametric Regression - A Simulation Experiment.
Sonderforschungsbereich 386, Discussion Paper 284
This paper considers an additive model y = f(x) + e when some observations on x are missing at random but corresponding observations on y are available. Especially for this model missing at random is an interesting case because of the fact that the complete case analysis is not expected to be suitable. A simulation study is reported and methods are compared based on superiority measures as the sample mean squared error, sample variance and estimated sample bias. In detail, complete case analysis, zero order regression plus random noise, single imputation and nearest neighbor imputation are discussed.