Applying Quantitative Bias Analysis to Epidemiologic Data (Hardcover, 2009 ed.)

, ,
Bias analysis quantifies the influence of systematic error on an epidemiology study's estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow.

R3,591

Or split into 4x interest-free payments of 25% on orders over R50
Learn more

Discovery Miles35910
Mobicred@R337pm x 12* Mobicred Info
Free Delivery
Delivery AdviceShips in 10 - 15 working days


Toggle WishListAdd to wish list
Review this Item

Product Description

Bias analysis quantifies the influence of systematic error on an epidemiology study's estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow.

Customer Reviews

No reviews or ratings yet - be the first to create one!

Product Details

General

Imprint

Springer-Verlag New York

Country of origin

United States

Series

Statistics for Biology and Health

Release date

May 2009

Availability

Expected to ship within 10 - 15 working days

First published

2009

Authors

, ,

Dimensions

235 x 155 x 25mm (L x W x T)

Format

Hardcover

Pages

192

Edition

2009 ed.

ISBN-13

978-0-387-87960-4

Barcode

9780387879604

Categories

LSN

0-387-87960-9



Trending On Loot