Applying Quantitative Bias Analysis to Epidemiologic Data (2nd ed. 2021) (Statistics for Biology and Health)

Synopsis

This textbook and guide focuses on methodologies for bias analysis in epidemiology and public health, not only providing updates to the first edition but also further developing methods and adding new advanced methods. As computational power available to analysts has improved and epidemiologic problems have become more advanced, missing data, Bayes, and empirical methods have become more commonly used. This new edition features updated examples throughout and adds coverage addressing: Measurement error pertaining to continuous and polytomous variables Methods surrounding person-time (rate) data Bias analysis using missing data, empirical (likelihood), and Bayes methods A unique feature of this revision is its section on best practices for implementing, presenting, and interpreting bias analyses. Pedagogically, the text guides students and professionals through the planning stages of bias analysis, including the design of validation studies and the collection of validity data from other sources. Three chapters present methods for corrections to address 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.

Copyright:

2021

Book Details

Book Quality:

Publisher Quality

ISBN-13:

9783030826734

Related ISBNs:

9783030826727

Publisher:

Springer International Publishing

Date of Addition:

04/24/22

Copyrighted By:

Springer Nature Switzerland AG

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Science, Social Studies, Mathematics and Statistics, Medicine

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.