This valuable book-length treatment of the field offers coverage of estimation for situations where the model variables are observed subject to measurement error. Included are regression models with errors in the variables, latent variable models, and factor models. Brings together results from several areas of application, including discussion of recent results for nonlinear models and for models with unequal variances. Also explained are the estimation of true values for the fixed model, prediction of true values under the random model, model checks, and the analysis of residuals. Procedures are illustrated with data drawn from nearly twenty real-data sets.