Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments

✍ Scribed by Paul Gustafson

Publisher: Chapman and Hall/CRC
Year: 2003
Tongue: English
Leaves: 188
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Mismeasurement of explanatory variables is a common hazard when using statistical modeling techniques, and particularly so in fields such as biostatistics and epidemiology where perceived risk factors cannot always be measured accurately. With this perspective and a focus on both continuous and categorical variables, Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments examines the consequences and Bayesian remedies in those cases where the explanatory variable cannot be measured with precision.The author explores both measurement error in continuous variables and misclassification in discrete variables, and shows how Bayesian methods might be used to allow for mismeasurement. A broad range of topics, from basic research to more complex concepts such as "wrong-model" fitting, make this a useful research work for practitioners, students and researchers in biostatistics and epidemiology."

📜 SIMILAR VOLUMES

Measurement Error and Misclassification

📁 Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments

✍ Paul Gustafson 📂 Library 📅 2004 🏛 Chapman and Hall/CRC 🌐 English

Statistical analysis with measurement er

📁 Statistical analysis with measurement error or misclassification strategy, method and application

✍ Yi, Grace Y 📂 Library 📅 2017 🏛 Springer, published by Springer Nature 🌐 English

<p>This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in vari

Bayesian Statistics and Marketing (Wiley

📁 Bayesian Statistics and Marketing (Wiley Series in Probability and Statistics)

✍ Peter E. Rossi, Greg M. Allenby, Rob McCulloch 📂 Library 📅 2006 🏛 Wiley 🌐 English

The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new p

Bayesian Analysis in Statistics and Econ

📁 Bayesian Analysis in Statistics and Econometrics

✍ Joseph B. Kadane, Parthasarathy Bagchi (auth.), Prem K. Goel, N. Sreenivas Iyeng 📂 Library 📅 1992 🏛 Springer-Verlag New York 🌐 English

<p>This volume is based on the invited and the contributed presentations given at the Indo-U.S. Workshop on Bayesian Analysis in Statistics and Econometrics (BASE), Dec. 19-23, 1988, held at the Hotel Taj Residency, Bangalore, India. The workshop was jointly sponsored by The Ohio State University, T

Mathematical and Statistical Approaches

📁 Mathematical and Statistical Approaches to AIDS Epidemiology

✍ Steven J. Schwager, Carlos Castillo-Chavez, Herbert Hethcote (auth.), Carlos Cas 📂 Library 📅 1989 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

<p>The 18 research articles of this volume discuss the major themes that have emerged from mathematical and statistical research in the epidemiology of HIV. The opening paper reviews important recent contributions. Five sections follow: Statistical Methodology and Forecasting, Infectivity and the HI

Contemporary Bayesian Econometrics and S

📁 Contemporary Bayesian Econometrics and Statistics (Wiley Series in Probability and Statistics)

✍ John Geweke 📂 Library 📅 2005 🌐 English