Description
Bayesian Methods for Repeated Measures
Chapman & Hall/CRC Biostatistics Series
Author: Broemeling Lyle D.
Language: EnglishSubjects for Bayesian Methods for Repeated Measures:
Keywords
BUGS CODE; SD Error; Bayesian analysis; Posterior Distribution; Bayesian inferential methods; Posterior Analysis; Bayesian regression techniques; Initial Values List; WinBUGS; Var Var Var Var Var; analysis of repeated measures; Random Effects Bi; biostatistics; Scatter Plot; linear models for repeated measures studies; Credible Interval; Multiple Linear Regression; MCMC Simulation; Unstructured Covariance Matrix; Posterior Median; Precision Matrix; Compound Symmetry; Cov Cov Cov; Repeated Measures; Lowess Curves; Repeated Measures Study; Missing Values; Missing Data; Gibbs Sequences; Plasma Concentration; DIC Ρm
Approximative price 148.11 €
In Print (Delivery period: 15 days).
Add to cart the book of Broemeling Lyle D.Publication date: 08-2015
· 15.6x23.4 cm · Hardback
Approximative price 71.13 €
In Print (Delivery period: 14 days).
Add to cart the book of Broemeling Lyle D.Publication date: 06-2018
· 15.6x23.4 cm · Paperback
Description
/li>Contents
/li>Biography
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Analyze Repeated Measures Studies Using Bayesian Techniques
Going beyond standard non-Bayesian books, Bayesian Methods for Repeated Measures presents the main ideas for the analysis of repeated measures and associated designs from a Bayesian viewpoint. It describes many inferential methods for analyzing repeated measures in various scientific areas, especially biostatistics.
The author takes a practical approach to the analysis of repeated measures. He bases all the computing and analysis on the WinBUGS package, which provides readers with a platform that efficiently uses prior information. The book includes the WinBUGS code needed to implement posterior analysis and offers the code for download online.
Accessible to both graduate students in statistics and consulting statisticians, the book introduces Bayesian regression techniques, preliminary concepts and techniques fundamental to the analysis of repeated measures, and the most important topic for repeated measures studies: linear models. It presents an in-depth explanation of estimating the mean profile for repeated measures studies, discusses choosing and estimating the covariance structure of the response, and expands the representation of a repeated measure to general mixed linear models. The author also explains the Bayesian analysis of categorical response data in a repeated measures study, Bayesian analysis for repeated measures when the mean profile is nonlinear, and a Bayesian approach to missing values in the response variable.
Introduction to the Analysis of Repeated Measures. Review of Bayesian Regression Methods. Foundation and Preliminary Concepts. Linear Models for Repeated Measures and Bayesian Inference. Estimating the Mean Profile of Repeated Measures. Correlation Patterns for Repeated Measures. General Linear Mixed Model. Repeated Measures for Categorical Data. Nonlinear Models and Repeated Measures. Bayesian Techniques for Missing Data.
Lyle D. Broemeling has 30 years of experience as a biostatistician. He has been a professor at the University of Texas Medical Branch at Galveston, the University of Texas School of Public Health at Houston, and the University of Texas MD Anderson Cancer Center. He is also the author of several books, including Bayesian Methods in Epidemiology. His research interests include the analysis of repeated measures and Bayesian methods for assessing medical test accuracy and inter-rater agreement.