The Additive Model with Missing Values in the Independent Variable - Theory and Simulation

After a short introduction of the model, the missing mechanism and
the method of inference some imputation procedures are introduced
with special focus on the simulation experiment. Within this
experiment, the simple additive model y = f(x) + e is assumed to
have missing values in the independent variable according to MCAR.
Besides the well-known complete case analysis, mean imputation plus
random noise, a single imputation and two ways of nearest neighbor
imputation are used. These methods are compared within a simulation
experiment based on the average mean square error, variances and
biases of \hat{f}(x) at the knots.