Measurement Error in Nonlinear Models

Raymond J. Carroll, David Ruppert, Leonard A. Stefanski (Autoren)

Buch | Hardcover

336 Seiten

1995
Chapman & Hall/CRC (Verlag)
978-0-412-04721-3 (ISBN)

Infos

This monograph is part of a series which focuses on statistics and applied probability. This volume concentrates on measurement error in nonlinear models.

---

This monograph provides an up-to-date discussion of analysis strategies for regression problems in which predictor variables are measured with errors. The analysis of nonlinear regression models includes generalized linear models, transform-both-sides models and quasilikelihood and variance function problems. The text concentrates on the general ideas and strategies of estimation and inference rather than being concerned with a specific problem. Measurement error occurs in many fields, such as biometry, epidemiology and economics. In particular, the book contains a large number of epidemiological examples. An outline of strategies for handling progressively more difficult problems is also provided.

Inhalt

Preface
Guide to Notation
1.Introduction
2.Regression and Attenuation
3.Regression Calibration
4.Simulation Extrapolation
5.Instrumental Variables
6.Functional Methods
7.Likelihood and Quasilikelihood
8.Bayesian Methods
9.Semiparametric Methods
10.Unknown Link Functions
11.Hypothesis Testing
12.Density Estimation and Nonparametric Regression
13.Response Variable Error
14.Other Topics
Appendix: Fitting Methods and Models
References
Author Index
Subject Index

Produkt-Details

• Erscheint lt. Verlag: 6.7.1995
• Reihe/Serie: Chapman & Hall/CRC Monographs on Statistics & Applied Probability
• Sprache: englisch
• Maße: 152 x 229 mm
• Gewicht: 562 g
• Einbandart: Paperback
• Themenwelt: Mathematik / Informatik ► Mathematik
• ISBN-10: 0-412-04721-7 / 0412047217
• ISBN-13: 978-0-412-04721-3 / 9780412047213
• Zustand: Neuware