Continuing to focus on analytic strategies for regression problems for practical situations in which predictors are measured with error, this edition includes developments across the last decade, including greatly expanded discussion and applications of Bayesian computation through chain Monte Carlo techniques, a new chapter on longitudinal data and mixed models, and new material on nonparametric regression, density estimation, survival analysis, and score functions, with unique data sets available online. Topics include foundation concepts, including models and sources of data, linear regression and attenuation, regression calibrations, simulation extrapolation, instrumental variables, score function methods, likelihood and "quasilikelihood," Bayesian methods, hypothesis testing, nonparametric estimation, semiparametric regression, survival data, and response variable error. Appendices include background material and technical details, and all chapters have bibliographic notes. Annotation ©2006 Book News, Inc., Portland, OR (booknews.com)