Measurement Error in Nonlinear Models : A Modern Perspective, Second Edition

David Ruppert

ISBN 10: 1584886331 / ISBN 13: 9781584886334

Published by Chapman And Hall/CRC, 2006

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Written by leading authorities in nonlinear regression modeling, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition provides an up-to-date overview of analysis strategies for regression models in which variables are measured with errors. Thoroughly revised, this second edition includes additional material on Bayesian methods and semiparametric regression and a new chapter on generalized linear mixed models. Focusing on general ideas and strategies of estimation and inference, the authors provide various detailed worked examples, computed using MATLAB and R, from the fields of epidemiology and biometry. Data sets and software for all of the examples are available for download from the Internet.

Seller Inventory # 9781584886334

Bibliographic Details

• Title: Measurement Error in Nonlinear Models : A Modern Perspective, Second Edition
• Publisher: Chapman And Hall/CRC
• Publication Date: 2006
• Language: English
• ISBN 10: 1584886331
• ISBN 13: 9781584886334
• Binding: Buch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 235W x 157H x 30D millimeters 235 millimeters width by 157 millimeters height by 30 millimeters depth
• Weight: 845 grams

About this title

Synopsis

It’s been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and extensively updated to offer the most comprehensive and up-to-date survey of measurement error models currently available.

What’s new in the Second Edition?

· Greatly expanded discussion and applications of Bayesian computation via Markov Chain Monte Carlo techniques

· A new chapter on longitudinal data and mixed models

· A thoroughly revised chapter on nonparametric regression and density estimation

· A totally new chapter on semiparametric regression

· Survival analysis expanded into its own separate chapter

· Completely rewritten chapter on score functions

· Many more examples and illustrative graphs

· Unique data sets compiled and made available online

In addition, the authors expanded the background material in Appendix A and integrated the technical material from chapter appendices into a new Appendix B for convenient navigation. Regardless of your field, if you’re looking for the most extensive discussion and review of measurement error models, then Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition is your ideal source.

About the Author

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