Cantitate/Preț
Produs
Total produse
Vezi coșul
Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments de Paul Gustafson

Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments: Chapman & Hall/CRC Interdisciplinary Statistics

Autor Paul Gustafson
en Limba Engleză Hardback – 25 sep 2003
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."
Citește tot Restrânge

Din seria Chapman & Hall/CRC Interdisciplinary Statistics

Preț: 108546 lei

Preț vechi: 132374 lei
-18% Nou

Puncte Express: 1628
Preț estimativ în valută:
20780€ • 21632$ • 17107£

Carte tipărită la comandă

Livrare economică 01-15 februarie 25

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781584883357
ISBN-10: 1584883359
Pagini: 200
Ilustrații: 100 equations; 20 Tables, black and white; 39 Illustrations, black and white
Dimensiuni: 156 x 234 x 16 mm
Greutate: 0.42 kg
Ediția:UK edition
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Interdisciplinary Statistics

Public țintă

Professional

Cuprins

Introduction. Impact of Mismeasured Continuous Variables. Impact of Mismeasured Categorical Variables. Adjustment for Mismeasured Continuous Variables. Adjustment for Mismeasured Categorical Variables. Further Topics. Appendix: Bayes-MCMC Inference. References.

Notă biografică

Paul Gustafson (University of British Columbia, Vancouver, Canada) (Author)

Recenzii

"The topic addressed by this book is an important one. … This book shows that error-prone measurements may create serious biases and offers Bayesian approaches to attempt unbiased estimation, or 'adjustments'. … This is a useful book if you have data containing errors or if you have an interest in statistical theory of errors of measurement. As nearly all data is in some way erroneous, it is a useful book for all statisticians and mathematically inclined epidemiologists. …"
-Statistics in Medicine, Vol. 24, 2005

"This book provides a good overview of recent topics in measurement error models in the linear and logistic regression context using the Bayesian paradigm… . "
-Technometrics

" … a welcome addition for anyone who is interested in the topic of mismeasurement and in particular the issue of Bayesian adjustment methods. Although it does not shy away from the theoretical issues surrounding this subject, it remains accessible for practical applied statisticians. The book has two real highlights for me: firstly, the author's focus on the problems that mismeasurement creates in a variety of complex situations, reflecting what practical statisticians deal with regularly. Secondly, the book gives almost equal treatment to the problem of mismeasurement of continuous and discrete variable; it is quite rare to see such extensive treatment of both situations in one place …The examples that are used throughout the book offer great insight, as they highlight the complexities of real life data analysis when mismeasurement is an issue …"
-Journal of the Royal Statistical Society, Series A, Vol. 157(3)

"This is a well-written book and contains a great deal of information on the impact of measurement error in explanatory variables, as well as details of methods to adjust for mismeasurement. Considering measurement error in both continuous and categorical variables, as well as using Bayesian methods to adjust for mismeasurement, make this an excellent resource for epidemiologists or medical statisticians."
-Zoe Fewell, International Journal of Epidemiology

"This book is an ambitious undertaking by a prolific, creative, and relatively young researcher. As a non-Bayesian researcher in the field on measurement error and misclassification, I found the book to be clearly written, well organized, and much interest. In fact, I enjoyed reading it. … I found this to be an interesting and clearly written text of high technical quality that would be of interest to statistical researchers in the measurement error and misclassification area as well as to Bayesian statisticians interested in a somewhat novel area of application for Bayesian statistics. All of us working in these areas should find this book a worthwhile read."
- Donna Spiegelman (Harvard School of Public Health), Journal of the American Statistical Association

Descriere

This book addresses statistical challenges posed by inaccurately measuring explanatory variables, a common problem in biostatistics and epidemiology. The author explores both measurement error in continuous variables and misclassification in categorical variables. He also describes the circumstances in which it is necessary to explicitly adjust for imprecise covariates using the Bayesian approach and a Markov chain Monte Carlo algorithm. The book offers a mix of basic and more specialized topics and provides mathematical details in the final sections of each chapter. Because of its dual approach, the book is a useful reference for biostatisticians, epidemiologists, and students.