1 Introduction | 1.1 Available methods | 1.2 Assumptions | 1.3 The role of the data analyst | 1.4 Additional information | 2 Multivariate outlier detection | 2.1 Bushfire data | 2.1.1 Data preparation | 2.1.2 Outlier detection | 2.1.3 Diagnostics | 2.2 Philips data | 3 Robust linear regression | 3.1 Model fit | 3.2 Tuning | 3.3 Model diagnostics | References | Notes

Outline | 1 Getting started | 2 Exploring the data | 3 Model specification | 4 Parameter estimation | 4.1 Maximum-likelihood estimation | 4.2 Huber-type M-estimation | Safe mode | 5 (Robust) prediction of the area-level means | 6 Mean square prediction error | References | Appendix | A Failure of convergence

Outline | Estimating methods | Population characteristics | Type of implementation | Preparations | 1 LOS (Length-of-stay) Hospital Data | 1.1 Survey design object | 1.2 Exploring the data | 2 Trimming | 2.1 Bare-bone methods | 2.2 Survey methods | 3 Winsorization | 3.1 Bare-bone methods | 3.2 Survey methods | 4 Weight Reduction Methods | 4.2 Survey methods | 5 M-Estimation | 5.1 Bare-bone methods | 5.2 Survey methods | 5.3 Adaptive estimation | 6 Utility Functions | 6.1 Weighted quantile and median | 6.2 Weighted MAD: median absolute deviation | 6.3 Weighted IQR: interquartile range | Notes | Bibliographical notes | References

Outline | 1 Preparations | 2 Robust ratio prediction | 2.1 Ratio predictor | 2.2 Robust ratio predictor | 3 Robust generalized regression prediction | 3.1 GREG | 3.2 Robust GREG | References

Outline | 1. Workplace Data | 1.1 Survey design object | 1.2 Exploring the data | 2 Robust Horvitz-Thompson Estimator | 2.1 Bare-bone methods | 2.2 Survey methods | 2.3 Adaptive estimation | References

Outline | 1 Preparations | 1.2 Goal | 1.3 Sampling design | 1.4 Exploring the data | 2 Design-based inference | 2.1 Heteroscedasticity | 2.2 Regression M-estimator | 2.3 Regression GM-estimator | Preparation | Robust Mahalanobis distances | Regression estimation and inference | 3 Model-based inference | 4 Compound design- and model-based inference | 4.1 The MU284 population | 4.2 Model fit and statistical inference | References