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Applying quantitative bias analysis ...

Fox, Matthew P.

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Applying quantitative bias analysis to epidemiologic data

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Applying quantitative bias analysis to epidemiologic data/ by Matthew P. Fox, Richard F. MacLehose, Timothy L. Lash.
作者:	Fox, Matthew P.
其他作者:	MacLehose, Richard F.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	1 online resource (xvi, 467 p.) :ill. (some col.), digital ;24 cm.
內容註:	1. Introduction and Objectives -- 2. A Guide to Implementing Quantitative Bias Analysis -- 3. Data Sources for Bias Analysis -- 4. Selection Bias -- 5. Uncontrolled Confounders -- 6. Misclassification -- 7. Measurement Error for Continuous Variables -- 8. Multiple Bias Modeling -- 8. Bias Analysis by Simulation for Summary Level Data -- 9. Bias Analysis by Simulation for Record Level Data -- 10. Combining Systematic and Random Error -- 11. Bias Analysis by Missing Data Methods -- 12. Bias Analysis by Empirical Methods -- 13. Bias Analysis by Bayesian Methods -- 14. Multiple Bias Modeling -- 15. Good Practices for Quantitative Bias Analysis -- 15. Presentation and Inference -- References -- Index.
Contained By:	Springer Nature eBook
標題:	Epidemiology - Research. -
電子資源:	https://doi.org/10.1007/978-3-030-82673-4
ISBN:	9783030826734

Applying quantitative bias analysis to epidemiologic data
Fox, Matthew P.

Applying quantitative bias analysis to epidemiologic data[electronic resource] /by Matthew P. Fox, Richard F. MacLehose, Timothy L. Lash. - Second edition. - Cham :Springer International Publishing :2021. - 1 online resource (xvi, 467 p.) :ill. (some col.), digital ;24 cm. - Statistics for biology and health,2197-5671. - Statistics for biology and health..

1. Introduction and Objectives -- 2. A Guide to Implementing Quantitative Bias Analysis -- 3. Data Sources for Bias Analysis -- 4. Selection Bias -- 5. Uncontrolled Confounders -- 6. Misclassification -- 7. Measurement Error for Continuous Variables -- 8. Multiple Bias Modeling -- 8. Bias Analysis by Simulation for Summary Level Data -- 9. Bias Analysis by Simulation for Record Level Data -- 10. Combining Systematic and Random Error -- 11. Bias Analysis by Missing Data Methods -- 12. Bias Analysis by Empirical Methods -- 13. Bias Analysis by Bayesian Methods -- 14. Multiple Bias Modeling -- 15. Good Practices for Quantitative Bias Analysis -- 15. Presentation and Inference -- References -- Index.

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.

ISBN: 9783030826734

Standard No.: 10.1007/978-3-030-82673-4doiSubjects--Topical Terms:

797712
Epidemiology
--Research.

LC Class. No.: RA652

Dewey Class. No.: 614.4072

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