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Bayesian methods for repeated measures / Lyle D. Broemeling.

By: Material type: TextTextSeries: Chapman & Hall/CRC biostatistics seriesPublication details: Boca Raton : CRC Press, ©2016.Description: xv, 552 p. : illustrations ; 25 cmISBN:
  • 9781482248197 (hardcover : acidfree paper)
Subject(s): DDC classification:
  • 000SB:570 23 B865
Contents:
1. Introduction to the analysis of repeated measures -- 2. Review of Bayesian regression methods -- 3. Foundation and preliminary concepts -- 4. Linear models for repeated measures and Bayesian inference -- 5. Estimating the mean profile of repeated measures -- 6. Correlation patterns for repeated measures -- 7. General mixed linear model -- 8. Repeated measures for categorical data -- 9. Nonlinear models and repeated measures -- 10. Bayesian techniques for missing data.
Summary: This book is intended to be a textbook for graduate students in statistics (including biostatistics) and as a fererence for consulting statisticians. It will be an invaluable resource especially for those involved in biostatistics, where use of repeated measures is common. The book adopts a practical approach and includes the WinBUGS code necessary to implement posterior analysis.
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Includes bibliographical references and index.

1. Introduction to the analysis of repeated measures --
2. Review of Bayesian regression methods --
3. Foundation and preliminary concepts --
4. Linear models for repeated measures and Bayesian inference --
5. Estimating the mean profile of repeated measures --
6. Correlation patterns for repeated measures --
7. General mixed linear model --
8. Repeated measures for categorical data --
9. Nonlinear models and repeated measures --
10. Bayesian techniques for missing data.

This book is intended to be a textbook for graduate students in statistics (including biostatistics) and as a fererence for consulting statisticians. It will be an invaluable resource especially for those involved in biostatistics, where use of repeated measures is common. The book adopts a practical approach and includes the WinBUGS code necessary to implement posterior analysis.

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