ABSTRACT
This is a book about measurement error in statistical analyses; what it is, how to model it, what the effects of ignoring it are and how to correct for it. In some sense, all statistical problems involve measurement error. For the purposes here, measurement error occurs whenever we cannot exactly observe one or more of the variables that enter into a model of interest. There are many reasons such errors occur, the most common ones being instrument error and sampling error. In this chapter we provide a collection of examples of potentially mismeasured variables, followed by a brief overview of the general structure and objectives in a measurement error problem, along with some basic terminology that appears throughout the book. Finally, we provide a road map for the rest of the book.
