Offers an overview of analysis strategies for regression models in which variables are measured with errors. This book includes material on Bayesian methods and semiparametric regression and a chapter on generalized linear mixed models.

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"I enjoyed reading this book and would recommend it to statisticians for their library." -Journal of Quality Technology ..."This present book is an essential purchase for the library and an excellent purchase for individuals." -International Statistical Institute ..."the book provides an up-to-date introduction to the application of MCMC methods. It is both readable and coherent and should form an essential addition to any modern applied statistician." -The Statistician "It has been a pleasure reading this book...the range of the authors appreciation of the actual issues and challenges pertaining to particular data sets, and extensive theoretical justification of estimation techniques is very impressive." -Biometrics

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Measurement Error in Nonlinear Models : A Modern Perspective

Carroll, Raymond J. (EDT); Ruppert, David; Stefanski, Leonard A.; Crainiceanu, Ciprian M.

Used - Hardcover

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