Bayesian Methods for Repeated Measures

by Lyle D. Broemeling

Overview

Analyze Repeated Measures Studies Using Bayesian TechniquesGoing 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,

Product Details

ISBN-13:	9781351231558
Publisher:	CRC Press
Publication date:	08/04/2015
Series:	Chapman & Hall/CRC Biostatistics Series
Sold by:	Barnes & Noble
Format:	eBook
Pages:	568
File size:	4 MB

About the Author

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.

Table of Contents

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.

Editorial Reviews

"The book will be especially useful for clinical researchers, epidemiologists, and other researchers focused on data analysis and seeking to apply Bayesian methods. Useful computer codes and worked examples are provided. Moreover, the book also has utility as a general exposition of data and graph analytic approaches to longitudinal data."
~Peter Congdon, Biometric Journal

"This book is rich in illustrative examples and detailed WinBUGS code for analyzing real-world data, while providing thorough insight in the underlying theory of Bayesian methods for the analysis of repeated measures data. This makes the book a practical guide, and a great resource for learning the theory and practice of Bayesian methods for repeated measures for students and applied statisticians."
~Hao Zhang

From the Publisher