ABSTRACT
The preceding four chapters were dedicated to the treatment of specific problems dealing with misclassification in categorical variables and additive measurement error in linear regression problems. Those settings allowed us to take an initial look at the key features in treating measurement error problems in relatively simple settings. This chapter provides a broader look at measurement error in general regression problems with subsequent chapters dedicated to application of the tools developed here to specific problems. The term regression is used here in a broad sense as the models presented can accommodate categorical or analysis of variance models, among others. In this chapter we:
1. Provide a quick review of regression models and methods of analysis without measurement error (Sections 6.2 and 6.3).
