Bayesian thinking in biostatistics

By:

Rosner, Gary L

Contributor(s):

Material type: Text

TextPublication details: CRC Press Boca Raton 2021Description: xix, 601 pISBN:

9781439800089

Subject(s):

Bayesian statistical decision theory

DDC classification:

570.15195 ROS

Summary: With a focus on incorporating sensible prior distributions and discussions on many recent developments in Bayesian methodologies, Bayesian Thinking in Biostatistics considers statistical issues in biomedical research. The book emphasizes greater collaboration between biostatisticians and biomedical researchers. The text includes an overview of Bayesian statistics, a discussion of many of the methods biostatisticians frequently use, such as rates and proportions, regression models, clinical trial design, and methods for evaluating diagnostic tests. Key Features Applies a Bayesian perspective to applications in biomedical science Highlights advances in clinical trial design Goes beyond standard statistical models in the book by introducing Bayesian nonparametric methods and illustrating their uses in data analysis Emphasizes estimation of biomedically relevant quantities and assessment of the uncertainty in this estimation Provides programs in the BUGS language, with variants for JAGS and Stan, that one can use or adapt for one's own research The intended audience includes graduate students in biostatistics, epidemiology, and biomedical researchers, in general.

List(s) this item appears in: Operation & quantitative Techniques | Marketing

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Operations Management & Quantitative Techniques	570.15195 ROS (Browse shelf(Opens below))	1	Available		004365

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Previous	530.11 RUS ABC of relativity	530.12 BOH Wholeness and the implicate order	530.12 CHA Quantum decision theory and complexity modelling in economics and public policy	570.15195 ROS Bayesian thinking in biostatistics	570.15195 TRI Biostatistics for the biological and health sciences	574.011 SIG Games of life: explorations in ecology, evolution, and behaviour	575 SMI Evolution and the theory of games	Next

Table of Contents
1. Scientific Data Analysis 2. Fundamentals I: Bayes Theorem, Knowledge Distributions, Prediction 3. Fundamentals II: Models for Exchangeable Observations 4. Computational Methods for Bayesian Analysis 5. Comparing Populations 6. Specifying Prior Distributions 7. Linear Regression 8. Binary Response Regression 9. Poisson and Non-linear Regression 10. Model Assessment 11Survival Modeling I: Models for Exchangeable Observations 12. Survival Modeling 2: Time-to-Event Regression Models 13. Clinical Trial Designs 14. Hierarchical Models and Longitudinal Data 15. Diagnostic Tests

With a focus on incorporating sensible prior distributions and discussions on many recent developments in Bayesian methodologies, Bayesian Thinking in Biostatistics considers statistical issues in biomedical research. The book emphasizes greater collaboration between biostatisticians and biomedical researchers. The text includes an overview of Bayesian statistics, a discussion of many of the methods biostatisticians frequently use, such as rates and proportions, regression models, clinical trial design, and methods for evaluating diagnostic tests.

Key Features

Applies a Bayesian perspective to applications in biomedical science
Highlights advances in clinical trial design
Goes beyond standard statistical models in the book by introducing Bayesian nonparametric methods and illustrating their uses in data analysis
Emphasizes estimation of biomedically relevant quantities and assessment of the uncertainty in this estimation
Provides programs in the BUGS language, with variants for JAGS and Stan, that one can use or adapt for one's own research
The intended audience includes graduate students in biostatistics, epidemiology, and biomedical researchers, in general.

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