Measurement Error in Nonlinear Models

Regular price €179.80
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Ciprian M. Crainiceanu
A01=David Ruppert
A01=Leonard A. Stefanski
A01=Raymond J. Carroll
Additive Measurement Error Model
advanced statistical modeling techniques
Author_Ciprian M. Crainiceanu
Author_David Ruppert
Author_Leonard A. Stefanski
Author_Raymond J. Carroll
Bayesian inference
berkson
Berkson Error Model
Berkson Errors
Berkson Model
calibration
Category=PBT
classical
Classical Error Model
Classical Measurement Error
Classical Measurement Error Model
Conditional Expectations
Data Set
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Error Model
Excess Relative Risk
FFQ
Full Conditional
generalized
Gibbs Sampler
idea
ignoring
instrumental variables
Linear Regression
logistic
longitudinal data modeling
Markov Chain Monte Carlo
Measurement Error
Measurement Error Models
Measurement Error Variance
Multiple Linear Regression
Naive Estimator
Nondifferential Measurement Error
nonparametric estimation
regression
Regression Calibration
Regression Calibration Approximation
Regression Calibration Model
Replicate Measurements
s2u
survival analysis
variance

Product details

  • ISBN 9781584886334
  • Weight: 1060g
  • Dimensions: 152 x 229mm
  • Publication Date: 21 Jun 2006
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

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.

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

More from this author