Visualization and Imputation of Missing Values

Preface.- 1 Topic-focused Introduction to R and Data Sets Used.- 2  Distribution, Pre-analysis of Missing Values and Data Quality.- 3  Detection of the Missing Values Mechanism with Tests and Models.- 4  Visualisation of Missing Values.- 5  General Considerations on Univariate Methods, Single and Multiple Imputation.- 6 Deductive Imputation and Outlier Replacement.- 7 Imputation Without a Model.- 8 Model-based Methods.- 9 Non-linear Methods.- 10 Methods for compositional data.- 11  Evaluation of the Quality of Imputation.- 12 Simulation of Data for Simulation Studies.