Applying Quantitative Bias Analysis to Epidemiologic Data

This textbook and guide provide updated methods for bias analysis in epidemiology and public health, including missing data, Bayes, and empirical methods. It also covers best practices for implementing, presenting, and interpreting bias analyses, with three chapters presenting methods for corrections to address selection bias, uncontrolled confounding, and measurement errors.

Format: Hardback
Length: 467 pages
Publication date: 25 March 2022
Publisher: Springer Nature Switzerland AG

This comprehensive textbook and guide delve into the realm of bias analysis in epidemiology and public health, offering not only an update to its first edition but also a significant expansion of methods and the introduction of advanced techniques. With the increasing computational power at the disposal of analysts and the complexity of epidemiologic challenges, the utilization of missing data, Bayes, and empirical methods has gained widespread popularity. This revised edition showcases updated examples throughout, providing a clear understanding of these methodologies. Furthermore, it delves into various topics, including measurement error related to continuous and polytomous variables, methods for handling person-time (rate) data, bias analysis employing missing data, empirical (likelihood), and Bayes methods, and a dedicated section on best practices for implementing, presenting, and interpreting bias analyses. Pedagogically, the text guides students and professionals through the intricate process of bias analysis, encompassing the design of validation studies and the acquisition of validity data from external sources.

Three chapters are dedicated to correcting selection bias, uncontrolled confounding, and measurement errors, and subsequent sections extend these methods to probabilistic bias analysis, missing data methods, likelihood-based approaches, Bayesian methods, and best practices.

By comprehensively covering these topics, this textbook serves as a valuable resource for researchers, practitioners, and students seeking to enhance their understanding and application of bias analysis in epidemiology and public health.

Weight: 856g
Dimension: 162 x 241 x 35 (mm)
ISBN-13: 9783030826727
Edition number: 2nd ed. 2021