Measurement Error: Models, Methods, and Applications

John P. Buonaccorsi

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March 2, 2010 by Chapman and Hall/CRC
Monograph - 463 Pages - 30 B/W Illustrations
ISBN 9781420066562 - CAT# C6656
Series: Chapman & Hall/CRC Interdisciplinary Statistics

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Features

  • Covers a wide array of statistical models, including misclassification in one- and two-way categorical tables, measurement error of various types in linear and nonlinear regression, measurement error in responses, mixed models, and time series
  • Describes common methods to correct for measurement error, such as SIMEX, regression calibration, likelihood-based techniques, and corrected estimating equations
  • Includes numerous worked examples using real-world data from epidemiology, ecology, and other disciplines

Summary

Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illustrates their application in various models. It describes the impacts of measurement errors on naive analyses that ignore them and presents ways to correct for them across a variety of statistical models, from simple one-sample problems to regression models to more complex mixed and time series models.

The book covers correction methods based on known measurement error parameters, replication, internal or external validation data, and, for some models, instrumental variables. It emphasizes the use of several relatively simple methods, moment corrections, regression calibration, simulation extrapolation (SIMEX), modified estimating equation methods, and likelihood techniques. The author uses SAS-IML and Stata to implement many of the techniques in the examples.

Accessible to a broad audience, this book explains how to model measurement error, the effects of ignoring it, and how to correct for it. More applied than most books on measurement error, it describes basic models and methods, their uses in a range of application areas, and the associated terminology.