When the independent variable is measured with error or when the model is misspecified by omitting important independent variables, least squares estimators will be biased. In such cases, the variance estimators are also biased. Methods for detecting model misspecification and estimation in measurement error models are discussed in later chapters. Also, the effect of overly influential data points and outliers is discussed later.